System

Abstract

A system is provided.SOLUTION: A system comprising: means for generating; means for collecting; means for automatically generating; means for converting to speech; and means for delivering.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] With conventional radio programs and news distribution services, users often receive a lot of unnecessary information, which they perceive as a waste of time. Furthermore, checking information while looking at a smartphone screen, known as "smartphone while sleeping," can lead to sleep deprivation and health problems. The objective of this invention is to provide a method for users to efficiently obtain the information they need and to prevent this from happening. [Means for solving the problem]

[0005] The present invention provides a system that uses generative AI to automatically generate radio-style scripts for the latest news and weather information based on a user's interests and schedule, and converts the generated scripts into audio for distribution. Specifically, the system solves this problem by providing a means for storing and analyzing user information, a means for collecting information from external sources, a means for editing the generated scripts, a means for transmitting audio data to the user's device, and a means for collecting and analyzing user feedback to improve the overall operation of the system.

[0006] The "means for generating" is a means for automatically generating a customized radio program script based on user interests and schedule information.

[0007] "Means of collection" refers to the means of collecting the latest news and weather information from external news APIs and weather information APIs.

[0008] "Automatic generation means" refers to a means of automatically generating radio program scripts for users using generative AI based on collected information.

[0009] The "means for converting into voice" refers to a means for using a TTS (Text-To-Speech) engine to convert the generated script into voice data.

[0010] "Means for distribution" refers to means for transmitting the generated audio data to the user's device.

[0011] "Means for storing and analyzing user information" refers to the means for storing the interests, schedule information, and past viewing history entered by the user in a database and analyzing this information.

[0012] "Means of collecting information from external sources" refers to means of accessing external news APIs or weather information APIs to obtain the latest information.

[0013] The "means for editing the generated script" refers to a means for editing the generated radio script as necessary and arranging it into an optimal format.

[0014] The "means for transmitting audio data to a user's device" refers to a means for delivering the generated audio data to a user's terminal and enabling streaming playback.

[0015] "Means for collecting and storing user feedback" refers to means for storing feedback provided by users in a database.

[0016] The "means for analyzing feedback and improving the overall operation of the system" refers to a means for analyzing collected feedback and improving the operation of the system and the script generation process. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9]1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0018] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0019] First, the terms used in the following description will be explained.

[0020] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0021] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0022] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0023] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0028] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0030] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0035] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0037] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0038] The present invention relates to a voice information provision system that allows users to efficiently obtain necessary information and prevents them from using their smartphones while sleeping. The system includes a generating means, a collecting means, an automatic generating means, a converting means to voice, a distributing means, a means for storing and analyzing user information, a means for collecting information from external sources, a means for editing the generated script, a means for transmitting voice data to the user's device, a means for collecting and storing user feedback, and a means for analyzing the feedback and improving the operation of the entire system.

[0039] 1. Entering and saving user information

[0040] User: Launches the radio app and accesses the account registration or login screen. Enters the news categories of interest (sports, entertainment, business, etc.) and daily schedule information.

[0041] Device: Sends information entered by the user (such as name, email address, and password), as well as interests and schedule information, to the server.

[0042] Server: Stores user information in a database and analyzes it.

[0043] 2. Collection of information

[0044] Server: Sends requests to external news and weather APIs to collect the latest news articles and weather information.

[0045] 3. Automatic Generation of Radio Programs

[0046] Server: Based on the user's saved interest and schedule information and past viewing history, generative AI is used to automatically generate radio program scripts suitable for the user.

[0047] 4. Convert to audio data

[0048] Server: The generated radio program script is converted into voice data using a TTS (Text-To-Speech) engine.

[0049] 5. Audio data distribution

[0050] Server: Sends the generated voice data to the user's device.

[0051] Device: Prepares the received audio data for playback, allowing users to listen to radio-style audio content through the app.

[0052] 6. Feedback Collection and Analysis

[0053] Users: After listening to the audio content, they provide feedback and ratings within the app.

[0054] Terminal: Sends the entered feedback to the server.

[0055] Server: Feedback information is stored in a database and analyzed to improve the system's operation and the script generation process.

[0056] For example, when a user wakes up in the morning, they launch a radio app on their smartphone. The device starts playing an automatically generated radio program along with a friendly message like "Good morning, user." The server generates the script for this radio program based on the latest news, weather information, and the user's schedule (e.g., work meetings). By listening to this, the user can efficiently obtain the information they need without having to look at their smartphone screen.

[0057] This system prevents users from using their smartphones while sleeping and allows them to efficiently obtain the information they need.

[0058] The processing flow will be explained below.

[0059] Step 1:

[0060] User: Launches the radio app and accesses the account registration or login screen. Enters the news category of interest (sports, entertainment, business, etc.), daily schedule information, name, email address, and password.

[0061] Step 2:

[0062] Terminal: Sends information entered by the user to the server, including name, email address, password, news category, and schedule information.

[0063] Step 3:

[0064] Server: Stores and analyzes user information in a database. Updates user profiles based on interests and schedule information.

[0065] Step 4:

[0066] Server: Sends requests to external news and weather APIs to collect the latest news articles and weather information.

[0067] Step 5:

[0068] Server: Using AI technology, the server automatically generates radio program scripts tailored to each user based on their saved interests, schedule, and past listening history. The scripts include greeting messages, the latest news, weather information, and schedule reminders.

[0069] Step 6:

[0070] Server: The generated radio program script is converted into voice data using a TTS (Text-To-Speech) engine.

[0071] Step 7:

[0072] Server: Sends the generated voice data to the user's device.

[0073] Step 8:

[0074] Device: Prepares to play the received audio data, allowing users to listen to radio-style audio content through the app.

[0075] Step 9:

[0076] Users: After listening to the audio content, they provide feedback and ratings within the app.

[0077] Step 10:

[0078] Terminal: Sends the entered feedback to the server.

[0079] Step 11:

[0080] Server: Feedback information is stored in a database and analyzed to improve the system's operation and the script generation process.

[0081] Example 1

[0082] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0083] In modern society, many users use smartphones to gather information, but in certain situations (e.g., using a smartphone while lying down), it can be difficult to see the screen. This situation can have a negative impact on users' lifestyles and health. Furthermore, it can be difficult to select and efficiently gather information, making it difficult for users to quickly obtain the information they need.

[0084] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0085] In this invention, the server includes means for saving and analyzing information entered by the user, means for collecting data from external information sources, means for generating a script based on the collected data, means for converting the generated script into audio data, and means for delivering the audio data, thereby enabling the user to efficiently obtain necessary information by voice without looking at the screen.

[0086] "Means for storing and analyzing information entered by users" refers to a device or system that stores data entered by users, such as personal information, interests, and schedules, analyzes that data, and uses it to generate appropriate content.

[0087] A "means for collecting data from external sources" is a device or system that collects up-to-date information from external data sources such as news APIs or weather APIs.

[0088] "Means for generating scripts based on collected data" refers to a device or system that automatically creates appropriate radio program scripts for users using a generative AI model based on collected news, weather information, etc.

[0089] The "means for converting the generated script into voice data" refers to a device or system that converts the generated text-format script into voice data using a TTS (Text-to-Speech) engine.

[0090] "Means for distributing audio data" refers to a device or system that transmits the converted audio data to the user's terminal so that it can be played back.

[0091] "Means for editing a generated script" refers to a device or system that manually or automatically modifies and edits an automatically generated script.

[0092] "Feedback collection and storage means" means a device or system that collects and stores user ratings and opinions within the app.

[0093] A "means for analyzing feedback and improving overall system operation" is a device or system that analyzes collected feedback information and optimizes system operation or the content generation process based on that information.

[0094] "Server" refers to a central processing unit or the entire system for executing and managing all of the above means.

[0095] The present invention is a voice information provision system that allows users to efficiently obtain necessary information and prevents them from using their smartphones while sleeping. This system includes processes from user information input to voice data delivery and even feedback collection and analysis. Specific embodiments of the system are described below.

[0096] Feature Overview

[0097] 1. Entering and saving user information

[0098] User: Using a device such as a smartphone or tablet, the user launches a radio app and accesses the account registration or login screen, where they enter their name, email address, password, or the news category of their interest (e.g., sports, entertainment, business), as well as their daily schedule information.

[0099] Terminal: Validates the information entered by the user to ensure it is in the correct format, then sends this information to the server.

[0100] Server: Receives the transmitted information and stores it in a database. The stored information is used in the next process.

[0101] 2. Collection of information

[0102] Server: Sends requests to external news APIs (e.g., Google News API) or weather APIs (e.g., OpenWeatherMap API) and collects the necessary data.

[0103] 3. Automatic Generation of Radio Programs

[0104] Server: Based on the collected data, a generative AI model (e.g., OpenAI GPT-4) is used to automatically generate a radio program script. The following are examples of prompts for the AI ​​model:

[0105] User name: Yamada Taro

[0106] Interesting news categories: Business, Technology

[0107] Daily schedule: Meeting at 8am

[0108] Prompt statement:

[0109] "Generate a morning news radio show for user Taro Yamada. The categories are business and technology, and the schedule includes a meeting at 8am."

[0110] 4. Convert to audio data

[0111] Server: The generated radio program script is converted into audio data using a TTS (Text-To-Speech) engine (e.g., Google Text-to-Speech API).

[0112] 5. Audio data distribution

[0113] Server: Sends the generated voice data to the user's device.

[0114] Device: Receives audio data, prepares it for playback, and allows users to listen to radio-style audio content through the app.

[0115] 6. Feedback Collection and Analysis

[0116] Users: After listening to the audio content, they provide feedback and ratings within the app.

[0117] Terminal: Sends the entered feedback to the server.

[0118] Server: Stores the feedback information in a database and analyzes it. Based on the analysis results, the overall system behavior and content generation process are improved.

[0119] Specific examples

[0120] When a user wakes up in the morning, they launch the radio app on their smartphone. The device starts playing an automatically generated radio program along with a friendly message like "Good morning, user." The server generates the script for this radio program based on the latest news, weather information, and the user's schedule (e.g., work meetings). By listening to this, users can efficiently obtain the information they need without looking at their smartphone screen. This system prevents users from "using their smartphone while sleeping" and allows them to efficiently obtain the information they need.

[0121] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0122] System processing steps

[0123] Step 1: Enter and save user information

[0124] User: Launches a radio app using a smartphone or tablet device, accesses the account registration or login screen, and enters their name, email address, password, news categories of interest (e.g., sports, entertainment, business), and daily schedule information.

[0125] Input: Personal information, interests, and schedule information entered by the user.

[0126] Output: Information entered into the terminal is saved.

[0127] Terminal: Validates the information entered by the user to ensure it is in the correct format, and after successful validation, sends the information to the server.

[0128] Input: Information entered by the user.

[0129] Data processing: Input validation (e.g., checking email address format, password strength).

[0130] Output: Information ready to be sent to the server.

[0131] Server: Receives the information sent from the device and stores it in a database, which makes the data available for subsequent processing.

[0132] Input: User information sent from the device.

[0133] Data processing: Data storage.

[0134] Output: User information stored in the database.

[0135] Step 2: Gather information

[0136] Server: Sends requests to external news and weather APIs to collect the latest news articles and weather information.

[0137] Input: Information sent in the API request (user interest categories and region information).

[0138] Data processing: Generating and sending API requests.

[0139] Output: Collected news articles and weather information.

[0140] Server: Analyzes the collected information and stores it in a database in the form of news titles, summaries, weather forecasts, etc.

[0141] Input: Collected news articles and weather information.

[0142] Data processing: Analyzing data and organizing them into categories.

[0143] Output: Information stored in a database after analysis.

[0144] Step 3: Automatic generation of radio programs

[0145] Server: Automatically generates radio program scripts using a generative AI model based on user information in the database and collected news and weather information.

[0146] Input: User interests, news, and weather information stored in a database.

[0147] Data processing: Creating and sending prompts to generative AI models.

[0148] Output: A radio show script generated by the generative AI model.

[0149] For example, the prompt:

[0150] User name: Yamada Taro

[0151] Interesting news categories: Business, Technology

[0152] Daily schedule: Meeting at 8am

[0153] Prompt statement:

[0154] "Generate a morning news radio show for user Taro Yamada. The categories are business and technology, and the schedule includes a meeting at 8am."

[0155] Step 4: Convert to audio data

[0156] Server: The generated radio program script is converted into voice data using a TTS (Text-To-Speech) engine.

[0157] Input: A generated radio script.

[0158] Data processing: Voice data generation using a TTS engine.

[0159] Output: The generated audio data.

[0160] Step 5: Streaming audio data

[0161] Server: Sends the generated voice data to the user's device.

[0162] Input: The generated audio data.

[0163] Data processing: Preparing and sending audio data for distribution.

[0164] Output: The audio data sent to the device.

[0165] Device: Receives audio data and prepares it for playback, allowing users to listen to radio-style audio content through the app.

[0166] Input: Audio data received from the server.

[0167] Data processing: preparing for playback (e.g., caching, storing in memory).

[0168] Output: The audio content that is played to the user.

[0169] Step 6: Collect and analyze feedback

[0170] Users: After listening to the audio content, they provide feedback and ratings within the app.

[0171] Input: User input, such as ratings and feedback.

[0172] Output: Feedback typed into the terminal.

[0173] Terminal: Sends the entered feedback to the server.

[0174] Input: User feedback.

[0175] Data processing: packaging and sending feedback.

[0176] Output: Feedback sent to the server.

[0177] Server: Stores the feedback information in a database and analyzes it. Based on the analysis results, the system's behavior and content generation process are improved.

[0178] Input: Feedback sent from the device.

[0179] Data processing: Analysis of feedback and storage in a database.

[0180] Output: Improvements to system behavior and content generation processes.

[0181] (Application example 1)

[0182] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0183] Conventional voice information systems require users to manually search for information, which reduces the efficiency of information gathering and use. There are also concerns about the negative health effects of using a smartphone while sleeping. Furthermore, there is a lack of personalized information provision tailored to individual user needs, creating a need for improved user experience.

[0184] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0185] In this invention, the server includes a means for generating prompt sentences for generating and delivering voice information, a means for utilizing a generative AI model for providing the voice information, and a means for adjusting the output content of the generative AI model using the results of the behavior analysis, thereby enabling efficient and personalized voice information delivery according to the user's needs.

[0186] "Generative means" is the ability to create new information or content for a specific purpose.

[0187] "Means of collecting information" refers to the function of obtaining necessary data and news from external sources.

[0188] "Means for automatic generation" refers to the ability of the system to autonomously create content without the need for human intervention.

[0189] "Means for converting into voice" refers to technology for converting text data into voice data.

[0190] "Means of distribution" refers to the function of delivering the generated voice data and information to the user's device.

[0191] "Means for generating prompt sentences for generating and delivering voice information" refers to a function that automatically generates initial input (prompts) for the generative AI model to create personalized voice information.

[0192] A "server" is a computer system that processes requested information and manages data.

[0193] "Means for saving and analyzing user information" refers to the function of saving user interests and schedule information in a database and analyzing it.

[0194] "Means of collecting information from external sources" refers to the ability to obtain necessary news and weather information from external APIs and databases.

[0195] "Means for editing the generated script" refers to a function for manually or automatically correcting and adjusting the generated content as needed.

[0196] "Means for transmitting voice data to the user's terminal" refers to a function for delivering the generated voice data to the user's smartphone or other device.

[0197] "Means of using a generative AI model to provide voice information" refers to technology that uses generative AI to generate voice information appropriate for the user.

[0198] "Means for collecting and storing user feedback" refers to a function that obtains user ratings and opinions and stores them in a database.

[0199] "Means for analyzing feedback and improving the overall operation of the system" refers to a function for analyzing collected feedback to improve system performance and user satisfaction.

[0200] "Means for adjusting the output content of the generative AI model using the results of behavior analysis" refers to a function that optimizes the parameters and output of the generative AI based on the analysis results.

[0201] This invention relates to a voice information providing system that allows users to efficiently obtain necessary information and prevent "smartphone use while sleeping." This system is realized by combining the following main functions.

[0202] First, the server collects user interest and schedule information, stores it in a database, and analyzes it. Users launch the radio app on their smartphone and input their news categories of interest (e.g., sports, entertainment, business, etc.) and daily schedule information. This identifies the user's individual needs.

[0203] The server then sends requests to external news and weather APIs to gather the latest news articles and weather information, which is then filtered based on the user's interests.

[0204] Based on the collected information, the server uses a generative AI model to automatically generate a personalized radio show script suitable for the user. The script is created by inputting the generative AI model using prompt sentences such as the following:

[0205] "User is interested in sports and entertainment. Generate a personalized newscast script with the latest news and this morning's schedule information."

[0206] The generated script is converted into audio data using a server-based text-to-speech (TTS) engine. In this case, we use Google Cloud Text-to-Speech.

[0207] The generated audio data is then sent from the server to the user's device, where it is prepared for playback by the smartphone app, allowing the user to listen to personalized radio-style audio content through the app.

[0208] Furthermore, after listening to the audio content, users can enter feedback and ratings within the app. The device then sends this feedback to the server, which then stores the feedback information in a database for analysis. The results of this analysis are used to adjust the generative AI model and improve the overall system's operation.

[0209] For example, when a user wakes up in the morning and launches the radio app on their smartphone, an automatically generated radio program will play along with a friendly message like, "Good morning, user." The server generates the script for this radio program based on the latest news, weather information, and the user's schedule (e.g., work meetings), allowing the user to efficiently obtain the information they need without having to look at their smartphone screen.

[0210] This system prevents users from using their smartphones while sleeping and allows them to efficiently obtain the information they need.

[0211] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0212] Step 1:

[0213] Collecting user information

[0214] A user opens a radio app on their smartphone and enters the news categories they are interested in (sports, entertainment, business, etc.) and their daily schedule information. This information is input data and is important for identifying the user's individual needs. This information is sent to a server for subsequent information collection and analysis.

[0215] Step 2:

[0216] Saving and analyzing user information

[0217] The server stores the information entered by the user (such as name, interests, schedule, etc.) in a database. This information is then analyzed and output to identify user interests and behavioral patterns. The results of this analysis are used in the next news gathering process.

[0218] Step 3:

[0219] Gathering external information

[0220] The server sends requests to external news and weather APIs to retrieve the latest news articles and weather information. This is the input data. The collected information is filtered based on the user's interests and stored in a database as personalized information. This is the output data.

[0221] Step 4:

[0222] Automatic generation of radio program scripts

[0223] The server automatically generates a radio show script using a generative AI model based on the saved user information and collected external information. Specifically, it inputs the following prompt sentences into the generative AI model (e.g., GPT-3):

[0224] "User is interested in sports and entertainment. Generate a personalized newscast script with the latest news and this morning's schedule information."

[0225] The generated script becomes the output data.

[0226] Step 5:

[0227] Script audio conversion

[0228] The server converts the generated radio program script into audio data using a TTS (Text-To-Speech) engine (e.g., Google Cloud Text-to-Speech). The input data is the generated script, and the output data is audio data. The audio data is optimized for user listening.

[0229] Step 6:

[0230] Audio data distribution

[0231] The server sends the audio data to the user's device. The device receives the audio data and prepares it for playback. The user can listen to personalized radio programs through the radio app. The delivery of the audio data is the output data.

[0232] Step 7:

[0233] Gathering feedback

[0234] After listening to the audio content, users enter their feedback and ratings within the app. This is the input data. This feedback is sent from the device to the server and stored in the database. This is the output data.

[0235] Step 8:

[0236] Analyzing feedback and improving the system

[0237] The server analyzes the collected feedback and adjusts the output of the generative AI model based on the results. This improves the overall operation of the system and enables the provision of voice information that better meets the user's needs. The analyzed feedback data is the output data.

[0238] The above are the specific processing steps of the system, which is a mechanism for efficiently providing personalized voice information to users.

[0239] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0240] The present invention relates to a voice information provision system that allows users to efficiently obtain necessary information and prevents them from using their smartphones while sleeping. The system includes a generating means, a collecting means, an automatic generating means, a converting means to voice, a distributing means, a means for storing and analyzing user information, a means for collecting information from external sources, a means for editing the generated script, a means for transmitting voice data to the user's device, a means for collecting and storing user feedback, a means for analyzing the feedback and improving the overall operation of the system, and an emotion engine for recognizing user emotions.

[0241] 1. Entering and saving user information

[0242] User: Launches the radio app and accesses the account registration or login screen. Enters the news category of interest (sports, entertainment, business, etc.), daily schedule information, name, email address, and password.

[0243] Terminal: Sends the information entered by the user (name, email address, password, news category, schedule information) to the server.

[0244] Server: Stores and analyzes user information in a database. Updates user profiles based on interests and schedule information.

[0245] 2. Collection of information

[0246] Server: Sends requests to external news and weather APIs to collect the latest news articles and weather information.

[0247] 3. Automatic Generation of Radio Programs

[0248] Server: Using AI generated from saved user interest and schedule information and past viewing history, the server automatically generates radio program scripts suited to the user.

[0249] 4. Convert to audio data

[0250] Server: The generated radio program script is converted into voice data using a TTS (Text-To-Speech) engine.

[0251] 5. Audio data distribution

[0252] Server: Sends the generated voice data to the user's device.

[0253] Device: Prepares the received audio data for playback, allowing users to listen to radio-style audio content through the app.

[0254] 6. Emotion Recognition by Emotion Engine

[0255] User: By providing voice input through the microphone while using the Radio app at designated times and events.

[0256] Device: Sends the user's voice input to the server.

[0257] Server: Using the emotion engine, recognize emotions from the user's voice input. The recognized emotions are stored in a database and reflected in the user profile.

[0258] 7. Adjust your script based on emotion

[0259] Server: Based on the user's emotional information, the generative AI adjusts the content of the radio program script. For example, if the user is feeling stressed, it will adjust the script to include more relaxing topics and music.

[0260] 8. Feedback Collection and Analysis

[0261] Users: After listening to the audio content, they provide feedback and ratings within the app.

[0262] Terminal: Sends the entered feedback to the server.

[0263] Server: Feedback information is stored in a database and analyzed to improve the system's operation and the script generation process.

[0264] For example, when a user wakes up in the morning, they launch a radio app on their smartphone. The device starts playing an automatically generated radio program along with a friendly message like "Good morning, user." The server generates a script for this radio program based on the latest news, weather information, and the user's schedule (e.g., work meetings). Furthermore, the emotion engine recognizes the user's emotions through their voice input and adjusts the script content based on those emotions. By listening to this, users can efficiently obtain the information they need without having to look at their smartphone screen.

[0265] This system prevents users from using their smartphones while sleeping and allows them to efficiently obtain the information they need. It also provides a more personalized experience by providing content that matches the user's emotions with an emotion engine.

[0266] The processing flow will be explained below.

[0267] Step 1:

[0268] User: Launches the radio app and accesses the account registration or login screen. Enters the news category of interest (sports, entertainment, business, etc.), daily schedule information, name, email address, and password.

[0269] Step 2:

[0270] Terminal: Sends information entered by the user to the server, including name, email address, password, news category, and schedule information.

[0271] Step 3:

[0272] Server: Stores and analyzes user information in a database. Updates user profiles based on interests and schedule information.

[0273] Step 4:

[0274] Server: Sends requests to external news and weather APIs to collect the latest news articles and weather information.

[0275] Step 5:

[0276] Server: Using AI technology to automatically generate radio program scripts tailored to each user based on their saved interests, schedule, and past listening history. The scripts include greeting messages, the latest news, weather information, and schedule reminders.

[0277] Step 6:

[0278] Server: The generated radio program script is converted into voice data using a TTS (Text-To-Speech) engine.

[0279] Step 7:

[0280] Server: Sends the generated voice data to the user's device.

[0281] Step 8:

[0282] Device: Prepares the received audio data for playback, allowing users to listen to radio-style audio content through the app.

[0283] Step 9:

[0284] User: By providing voice input through the microphone while using the Radio app at designated times and events.

[0285] Step 10:

[0286] Device: Sends the user's voice input to the server.

[0287] Step 11:

[0288] Server: Using the emotion engine, recognize emotions from the user's voice input. The recognized emotions are stored in a database and reflected in the user profile.

[0289] Step 12:

[0290] Server: Based on the user's emotional information, the generative AI adjusts the content of the radio program script. For example, if the user is feeling stressed, it will adjust the script to include more relaxing topics and music.

[0291] Step 13:

[0292] Terminal: Receives the voice data generated based on the contents of the readjusted script.

[0293] Step 14:

[0294] Device: Prepares for playback and allows the user to listen to tailored radio-style audio content.

[0295] Step 15:

[0296] Users: After listening to the audio content, they provide feedback and ratings within the app.

[0297] Step 16:

[0298] Terminal: Sends the entered feedback to the server.

[0299] Step 17:

[0300] Server: Feedback information is stored in a database and analyzed to improve the system's operation and the script generation process.

[0301] Example 2

[0302] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0303] In today's information society, users need ways to efficiently obtain the information they need. However, many users have the habit of staring at their smartphone screens for long periods of time, which can lead to health problems such as decreased eyesight and poor posture. Furthermore, there is a lack of personalized information delivery systems that match the interests and emotions of individual users. Therefore, there is a need for a system that can provide information tailored to each user's needs, prevent smartphone use while sleeping, and reduce the impact on health.

[0304] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a generation means, an information collection means, an automatic generation means, a voice conversion means, and a distribution means. This allows the user to efficiently obtain the necessary information without using their eyes. In addition, since the server includes an emotion recognition means that recognizes the user's emotion and a script adjustment means that adjusts the script content based on the recognized emotion, it is possible to provide personalized information and increase user satisfaction.

[0305] A "generation means" is a device or process that has the function of creating data or content based on specified information.

[0306] An "information gathering tool" is a device or process that obtains the required data from an external source.

[0307] An "automatic generation means" is a device or process that has the ability to automatically generate content using artificial intelligence or algorithms based on collected data and user information.

[0308] "Speech conversion means" means a device or process that converts generated text data into speech data, such as a text-to-speech (TTS) engine.

[0309] A "delivery mechanism" is a device or process that transmits generated or converted audio data to a user's device.

[0310] "User information storage means" refers to a device or process that has the function of storing information provided by a user in a database or the like.

[0311] An "external information gathering means" is a device or process that obtains the latest news, weather information, etc. from external sources.

[0312] "Script editing means" refers to a device or process that has the function of editing and adjusting the generated script based on the user's needs and feelings.

[0313] "Audio data transmission means" is a device or process capable of transmitting generated audio data to a user's device.

[0314] A "user feedback collection means" is a device or process that has the function of collecting user ratings and opinions.

[0315] "Feedback analysis means" refers to a device or process that has the function of analyzing collected user feedback and using it to improve the system.

[0316] "Emotion recognition means" refers to a device or process that has the function of determining emotions from user voice input, etc.

[0317] A "script adjustment means" is a device or process that has the function of adjusting the script content of a radio program based on the recognized emotional information.

[0318] The present invention relates to a voice information provision system that allows users to efficiently obtain necessary information and prevents "smartphone use while sleeping." The system includes a generation unit, an information collection unit, an automatic generation unit, a voice conversion unit, and a distribution unit. It also includes a user information storage unit, an external information collection unit, a script editing unit, a voice data transmission unit, a user feedback collection unit, a feedback analysis unit, an emotion recognition unit, and a script adjustment unit.

[0319] First, the information provided by the user is sent from the device to a server. The server stores this information in a database and updates the user profile. For example, a user enters their name, email address, news categories of interest, and schedule information into a radio app. This information is sent from the device to the server, which stores it in a database such as MySQL and analyzes it.

[0320] The server then sends requests to external news or weather APIs to gather the latest news articles or weather information. For example, an HTTP GET request can be used to retrieve the latest articles from an external news API.

[0321] The server inputs prompts into the AI ​​model based on the saved user information, past viewing history, and external information, and automatically generates a radio program script. For example, the prompt could be: "Generate a radio program script that includes the latest news and weather forecast based on the user's interests."

[0322] The generated script is converted into voice data using a TTS (Text-To-Speech) engine in a voice conversion means on the server, for example, by using the Google Text-to-Speech API.

[0323] The server then delivers the audio data to the user's device. The audio data file is sent via an HTTP response, and the device receives the audio data, prepares it for playback, and starts playback using the media player API.

[0324] Furthermore, when a user uses the radio app at a specified time or event and inputs voice data through the microphone, the device sends this voice data to the server. The server uses emotion recognition to recognize emotions from the user's voice input, stores them in a database, and reflects them in the user profile. Based on the recognized emotion information, it inputs prompts to the generative AI model, such as "The user is feeling stressed, so please adjust the script to include relaxing topics and music." This allows the script content to be adjusted appropriately.

[0325] Finally, after listening to the audio content, the user can provide feedback and ratings, which are then sent to the server, which stores the feedback information in a database and analyzes it to improve the system's operation and script generation process.

[0326] For example, when a user wakes up in the morning and launches a radio app on their smartphone, an automatically generated radio program is played along with a friendly message such as "Good morning, user." The program includes information such as "Today's weather is sunny. The temperature is 20 degrees, with a maximum temperature of 25 degrees. Also, there is a meeting at 3 pm today, so don't forget to get ready." When the user asks, "What do you think about today's news?", the system recognizes the user's emotions and provides more relaxing topics based on the results.

[0327] Example prompt sentence:

[0328] "Generate radio show scripts with breaking news and weather forecasts based on user interests."

[0329] In this way, users can efficiently obtain the information they need without looking at their smartphone screen, and can receive information that is tailored to their emotions.

[0330] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0331] Step 1:

[0332] The user launches the radio app and accesses the account registration screen or login screen. The user enters their name, email address, password, and news categories of interest (daily schedule information). This is the input information. The device sends the information entered by the user to the server. Specifically, it uses the REST API to send an HTTP POST request. At this time, the input data is the name, email address, password, news categories, and schedule information, and the output is an HTTP request containing this information.

[0333] Step 2:

[0334] The server stores the received user information in a database. Specifically, it uses a database such as MySQL to store the data using an INSERT query. It then updates the user profile based on this information. In this process, the input data is the user information sent from the device, and the output is the stored data and the updated user profile.

[0335] Step 3:

[0336] The server sends HTTP GET requests to external news APIs and weather information APIs to collect the latest news articles and weather information. The input data is the API request, and the output is the retrieved news articles and weather forecast data. This data is then analyzed within the server to extract the necessary information.

[0337] Step 4:

[0338] The server creates and inputs a prompt to the generative AI model based on user information, past viewing history, external information, etc. For example, the prompt might be, "Generate a radio program script that includes the latest news and weather forecast based on the user's interests." The input data is the user information and the prompt, and the output is the generated radio program script.

[0339] Step 5:

[0340] The server inputs the generated radio program script into a TTS (Text-To-Speech) engine and converts it into voice data. As a concrete example, we will use the Google Text-to-Speech API. The input data is the generated script, and the output is voice data generated by the TTS engine.

[0341] Step 6:

[0342] The server sends the generated audio data to the user's device. For example, it sends an audio data file as an HTTP response, and the device receives the audio data and prepares for playback. Specifically, it starts playback using a media player API. The input data is the audio data, and the output is the audio that is received and played.

[0343] Step 7:

[0344] The user uses the radio app at a designated time or event and inputs voice through the microphone. The device sends this voice input data to the server. The input data is the user's voice, and the output is the voice input data sent to the server.

[0345] Step 8:

[0346] The server uses emotion recognition means to recognize emotions from the user's voice input. For example, using an emotion analysis API, it obtains the result "The user is relaxed." The input data is the voice input data, and the output is the analyzed emotion information. This is saved in the database and reflected in the user profile.

[0347] Step 9:

[0348] The server inputs prompts to the generative AI model based on the recognized emotional information. For example, it might say, "The user is feeling stressed, so please adjust the prompts to include relaxing topics and music." The input data are the recognized emotional information and prompts, and the output is an adjusted radio program script.

[0349] Step 10:

[0350] After listening to the audio content, the user inputs feedback and ratings within the app. The device sends this feedback to the server. The input data is the feedback, and the output is the feedback data sent to the server.

[0351] Step 11:

[0352] The server stores the feedback information in a database and analyzes it, which improves the system's behavior and the generation process. The input data is the feedback information, and the output is the analysis results and a list of improvements.

[0353] This is the specific processing flow of this system. This series of steps allows users to efficiently obtain the information they need without using their vision, and also provides them with personalized information that matches their emotions.

[0354] (Application example 2)

[0355] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0356] In modern society, many people operate smart devices while lying down, which often leads to poor sleep quality and health problems. Furthermore, it is difficult to efficiently obtain necessary information, which contributes to stress in daily life. The purpose of this invention is to solve these problems and support a healthy lifestyle while enabling users to efficiently obtain necessary information.

[0357] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting and saving user information, means for collecting information from external information sources, means for automatically generating a radio program script based on the user's interests and schedule information, means for converting the generated script into audio data, means for distributing the audio data, means for recognizing emotions from the user's voice input, means for adjusting the script content based on the recognized emotions, and means for collecting and analyzing user feedback. This allows users to efficiently obtain necessary information without looking at the screen of their smart device, preventing them from using their smartphone while sleeping. Furthermore, providing personalized content based on emotions is expected to reduce stress and improve quality of life.

[0358] "Means for inputting and storing user information" refers to the means by which a user inputs information about their interests and schedule and stores it in a database.

[0359] "Means of collecting information from external sources" refers to means of collecting the latest information using APIs, etc., to obtain external news and weather information.

[0360] "Means for automatically generating radio program scripts based on user interests and schedule information" means means for a generative AI model to use user profile data to create radio program scripts that are appropriate for the user.

[0361] The "means for converting the generated script into voice data" refers to a means for converting the generated script in text form into voice data using a TTS (Text-To-Speech) engine.

[0362] "Means for distributing audio data" refers to means for transmitting the generated audio data to a user's smartphone or other device and distributing audio content.

[0363] The "means for recognizing emotions from user voice input" refers to a means for analyzing emotions from the user's voice using an emotion engine and acquiring emotion data.

[0364] "Means for adjusting script content based on recognized emotions" refers to a means by which the generative AI model dynamically changes the script content of a radio program based on the acquired emotional data.

[0365] "Means for collecting and analyzing user feedback" refers to the means for storing the ratings and opinions provided by users in a database and analyzing them to help improve the system.

[0366] This invention provides a voice information provision system that allows users to efficiently obtain necessary information and prevents excessive use of smart devices. The system generates personalized voice content based on the user's interests and schedule information, and adjusts the content by recognizing the user's emotions.

[0367] Hardware and Software Used

[0368] The system of the present invention uses a server, user devices (smartphones, tablets, etc.), and various APIs (news API, weather information API, etc.). The server performs the main processing and performs various data processing and calculations using advanced software tools such as generative AI models, TTS (Text-To-Speech) engines, and emotion recognition engines.

[0369] Processing flow

[0370] 1. User information input and storage:

[0371] The server stores the name, email address, interest categories, schedule information, etc. that the user entered when registering an account in a database. This information is analyzed by the server and reflected in the user profile.

[0372] 2. Collection of Information:

[0373] The server sends requests to external news and weather APIs to collect the latest news articles and weather information in real time.

[0374] 3. Automatic generation of radio program scripts:

[0375] Based on the collected information and the user's profile, the server uses a generative AI model to automatically generate a radio program script suitable for the user, including news related to the user's interests and necessary schedule information.

[0376] 4. Conversion to audio data:

[0377] The server converts the generated script into audio data using a TTS engine, which can be heard by the user without any visual intervention.

[0378] 5. Audio data delivery:

[0379] The server transmits the generated voice data to the user's terminal, and the terminal plays back the received voice data.

[0380] 6. Emotion recognition:

[0381] When a user makes a voice input, the device sends the voice data to the server, which uses an emotion engine to recognize the user's emotion from the voice data and stores the information in a database.

[0382] 7. Content adjustment based on emotions:

[0383] The server uses the generative AI model to adjust the radio program script based on the recognized emotion data, for example, by including more relaxing topics and music if the user is feeling stressed.

[0384] 8. Feedback Collection and Analysis:

[0385] After listening to the audio content, users can input feedback, which is then sent to the server, which then stores the collected feedback in a database and analyzes it to improve the overall operation of the system.

[0386] Examples and prompts

[0387] As a concrete example, the following shows a specific case where a news API and sentiment model are utilized.

[0388] 1. News gathering examples:

[0389] Send a request to the URL https: / / newsapi.org / v2 / top-headlines?country=jp&category=technology&apiKey=your_news_api_key to get the latest technology news.

[0390] 2. Example prompt sentences for emotion recognition model:

[0391] In response to a user's voice input of "How's the weather today?", the emotion recognition engine generates a script to reply, "The weather is sunny today. It looks like you'll have a pleasant time."

[0392] Through these steps, the system of the present invention can efficiently provide necessary information to users while promoting healthy device use.

[0393] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0394] Step 1:

[0395] A user uses a smart device to provide input information (name, email address, password, interest categories, schedule information) on an account registration screen or login screen. The device sends this input information to a server. The server stores the received user information in a database and analyzes the information to build a user profile. The input is the user information, and the output is the user profile stored in the database.

[0396] Step 2:

[0397] The server periodically sends requests to external APIs (such as news APIs and weather APIs) to collect the latest information based on the user's interests. This collected data is used to generate personalized information based on the user profile. The input is news and weather data retrieved from the APIs, and the output is the latest information stored on the server.

[0398] Step 3:

[0399] The server automatically generates radio show scripts using a generative AI model based on user interests and schedule information, including incorporating collected news and weather information and processing the data to reflect user interests. The inputs are the user profile and collected external data, and the output is the generated radio show script.

[0400] Step 4:

[0401] The server converts the generated radio program script into voice data using a TTS (Text-To-Speech) engine, which generates natural-sounding voice from the text data. The input is the generated script text, and the output is the generated voice data.

[0402] Step 5:

[0403] The server sends the generated audio data to the user's device. The device prepares the received audio data for playback, allowing the user to listen to the audio content through the app. The input is the generated audio data, and the output is the audio data sent to the user's device.

[0404] Step 6:

[0405] While listening to audio content, a user provides emotional information through voice input. The device sends this voice data to a server, which then uses an emotion engine to recognize the user's emotion and stores the information in a database. The input is the user's voice input, and the output is the recognized emotional data.

[0406] Step 7:

[0407] The server uses the recognized emotion data to tailor the radio show script using a generative AI model. For example, if the user's stress level is high, the server might include more relaxing topics and music. The input is the recognized emotion data, and the output is the tailored radio show script.

[0408] Step 8:

[0409] After listening to the audio content, the user inputs feedback. The terminal sends this feedback information to the server, which then stores the collected feedback in a database and analyzes it to improve the system's operation and the script generation process. The input is the user's feedback, and the output is the feedback information stored in the database and its analysis results.

[0410] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0411] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0412] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0413] [Second embodiment]

[0414] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0415] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0416] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0417] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0418] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0419] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0420] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0421] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0422] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0423] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0424] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0425] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0426] The present invention relates to a voice information provision system that allows users to efficiently obtain necessary information and prevents them from using their smartphones while sleeping. The system includes a generating means, a collecting means, an automatic generating means, a converting means to voice, a distributing means, a means for storing and analyzing user information, a means for collecting information from external sources, a means for editing the generated script, a means for transmitting voice data to the user's device, a means for collecting and storing user feedback, and a means for analyzing the feedback and improving the operation of the entire system.

[0427] 1. Entering and saving user information

[0428] User: Launches the radio app and accesses the account registration or login screen. Enters the news categories of interest (sports, entertainment, business, etc.) and daily schedule information.

[0429] Device: Sends information entered by the user (such as name, email address, and password), as well as interests and schedule information, to the server.

[0430] Server: Stores user information in a database and analyzes it.

[0431] 2. Collection of information

[0432] Server: Sends requests to external news and weather APIs to collect the latest news articles and weather information.

[0433] 3. Automatic Generation of Radio Programs

[0434] Server: Based on the user's saved interest and schedule information and past viewing history, generative AI is used to automatically generate radio program scripts suitable for the user.

[0435] 4. Convert to audio data

[0436] Server: The generated radio program script is converted into voice data using a TTS (Text-To-Speech) engine.

[0437] 5. Audio data distribution

[0438] Server: Sends the generated voice data to the user's device.

[0439] Device: Prepares the received audio data for playback, allowing users to listen to radio-style audio content through the app.

[0440] 6. Feedback Collection and Analysis

[0441] Users: After listening to the audio content, they provide feedback and ratings within the app.

[0442] Terminal: Sends the entered feedback to the server.

[0443] Server: Feedback information is stored in a database and analyzed to improve the system's operation and the script generation process.

[0444] For example, when a user wakes up in the morning, they launch a radio app on their smartphone. The device starts playing an automatically generated radio program along with a friendly message like "Good morning, user." The server generates the script for this radio program based on the latest news, weather information, and the user's schedule (e.g., work meetings). By listening to this, the user can efficiently obtain the information they need without having to look at their smartphone screen.

[0445] This system prevents users from using their smartphones while sleeping and allows them to efficiently obtain the information they need.

[0446] The processing flow will be explained below.

[0447] Step 1:

[0448] User: Launches the radio app and accesses the account registration or login screen. Enters the news category of interest (sports, entertainment, business, etc.), daily schedule information, name, email address, and password.

[0449] Step 2:

[0450] Terminal: Sends information entered by the user to the server, including name, email address, password, news category, and schedule information.

[0451] Step 3:

[0452] Server: Stores and analyzes user information in a database. Updates user profiles based on interests and schedule information.

[0453] Step 4:

[0454] Server: Sends requests to external news and weather APIs to collect the latest news articles and weather information.

[0455] Step 5:

[0456] Server: Using AI technology, the server automatically generates radio program scripts tailored to each user based on their saved interests, schedule, and past listening history. The scripts include greeting messages, the latest news, weather information, and schedule reminders.

[0457] Step 6:

[0458] Server: The generated radio program script is converted into voice data using a TTS (Text-To-Speech) engine.

[0459] Step 7:

[0460] Server: Sends the generated voice data to the user's device.

[0461] Step 8:

[0462] Device: Prepares to play the received audio data, allowing users to listen to radio-style audio content through the app.

[0463] Step 9:

[0464] Users: After listening to the audio content, they provide feedback and ratings within the app.

[0465] Step 10:

[0466] Terminal: Sends the entered feedback to the server.

[0467] Step 11:

[0468] Server: Feedback information is stored in a database and analyzed to improve the system's operation and the script generation process.

[0469] Example 1

[0470] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0471] In modern society, many users use smartphones to gather information, but in certain situations (e.g., using a smartphone while lying down), it can be difficult to see the screen. This situation can have a negative impact on users' lifestyles and health. Furthermore, it can be difficult to select and efficiently gather information, making it difficult for users to quickly obtain the information they need.

[0472] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0473] In this invention, the server includes means for saving and analyzing information entered by the user, means for collecting data from external information sources, means for generating a script based on the collected data, means for converting the generated script into audio data, and means for delivering the audio data, thereby enabling the user to efficiently obtain necessary information by voice without looking at the screen.

[0474] "Means for storing and analyzing information entered by users" refers to a device or system that stores data entered by users, such as personal information, interests, and schedules, analyzes that data, and uses it to generate appropriate content.

[0475] A "means for collecting data from external sources" is a device or system that collects up-to-date information from external data sources such as news APIs or weather APIs.

[0476] "Means for generating scripts based on collected data" refers to a device or system that automatically creates appropriate radio program scripts for users using a generative AI model based on collected news, weather information, etc.

[0477] The "means for converting the generated script into voice data" refers to a device or system that converts the generated text-format script into voice data using a TTS (Text-to-Speech) engine.

[0478] "Means for distributing audio data" refers to a device or system that transmits the converted audio data to the user's terminal so that it can be played back.

[0479] "Means for editing a generated script" refers to a device or system that manually or automatically modifies and edits an automatically generated script.

[0480] "Feedback collection and storage means" means a device or system that collects and stores user ratings and opinions within the app.

[0481] A "means for analyzing feedback and improving overall system operation" is a device or system that analyzes collected feedback information and optimizes system operation or the content generation process based on that information.

[0482] "Server" refers to a central processing unit or the entire system for executing and managing all of the above means.

[0483] The present invention is a voice information provision system that allows users to efficiently obtain necessary information and prevents them from using their smartphones while sleeping. This system includes processes from user information input to voice data delivery and even feedback collection and analysis. Specific embodiments of the system are described below.

[0484] Feature Overview

[0485] 1. Entering and saving user information

[0486] User: Using a device such as a smartphone or tablet, the user launches a radio app and accesses the account registration or login screen, where they enter their name, email address, password, or the news category of their interest (e.g., sports, entertainment, business), as well as their daily schedule information.

[0487] Terminal: Validates the information entered by the user to ensure it is in the correct format, then sends this information to the server.

[0488] Server: Receives the transmitted information and stores it in a database. The stored information is used in the next process.

[0489] 2. Collection of information

[0490] Server: Sends requests to external news APIs (e.g., Google News API) or weather APIs (e.g., OpenWeatherMap API) and collects the necessary data.

[0491] 3. Automatic Generation of Radio Programs

[0492] Server: Based on the collected data, a generative AI model (e.g., OpenAI GPT-4) is used to automatically generate a radio program script. The following are examples of prompts for the AI ​​model:

[0493] User name: Yamada Taro

[0494] Interesting news categories: Business, Technology

[0495] Daily schedule: Meeting at 8am

[0496] Prompt statement:

[0497] "Generate a morning news radio show for user Taro Yamada. The categories are business and technology, and the schedule includes a meeting at 8am."

[0498] 4. Convert to audio data

[0499] Server: The generated radio program script is converted into audio data using a TTS (Text-To-Speech) engine (e.g., Google Text-to-Speech API).

[0500] 5. Audio data distribution

[0501] Server: Sends the generated voice data to the user's device.

[0502] Device: Receives audio data, prepares it for playback, and allows users to listen to radio-style audio content through the app.

[0503] 6. Feedback Collection and Analysis

[0504] Users: After listening to the audio content, they provide feedback and ratings within the app.

[0505] Terminal: Sends the entered feedback to the server.

[0506] Server: Stores the feedback information in a database and analyzes it. Based on the analysis results, the overall system behavior and content generation process are improved.

[0507] Specific examples

[0508] When a user wakes up in the morning, they launch the radio app on their smartphone. The device starts playing an automatically generated radio program along with a friendly message like "Good morning, user." The server generates the script for this radio program based on the latest news, weather information, and the user's schedule (e.g., work meetings). By listening to this, users can efficiently obtain the information they need without looking at their smartphone screen. This system prevents users from "using their smartphone while sleeping" and allows them to efficiently obtain the information they need.

[0509] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0510] System processing steps

[0511] Step 1: Enter and save user information

[0512] User: Launches a radio app using a smartphone or tablet device, accesses the account registration or login screen, and enters their name, email address, password, news categories of interest (e.g., sports, entertainment, business), and daily schedule information.

[0513] Input: Personal information, interests, and schedule information entered by the user.

[0514] Output: Information entered into the terminal is saved.

[0515] Terminal: Validates the information entered by the user to ensure it is in the correct format, and after successful validation, sends the information to the server.

[0516] Input: Information entered by the user.

[0517] Data processing: Input validation (e.g., checking email address format, password strength).

[0518] Output: Information ready to be sent to the server.

[0519] Server: Receives the information sent from the device and stores it in a database, which makes the data available for subsequent processing.

[0520] Input: User information sent from the device.

[0521] Data processing: Data storage.

[0522] Output: User information stored in the database.

[0523] Step 2: Gather information

[0524] Server: Sends requests to external news and weather APIs to collect the latest news articles and weather information.

[0525] Input: Information sent in the API request (user interest categories and region information).

[0526] Data processing: Generating and sending API requests.

[0527] Output: Collected news articles and weather information.

[0528] Server: Analyzes the collected information and stores it in a database in the form of news titles, summaries, weather forecasts, etc.

[0529] Input: Collected news articles and weather information.

[0530] Data processing: Analyzing data and organizing them into categories.

[0531] Output: Information stored in a database after analysis.

[0532] Step 3: Automatic generation of radio programs

[0533] Server: Automatically generates radio program scripts using a generative AI model based on user information in the database and collected news and weather information.

[0534] Input: User interests, news, and weather information stored in a database.

[0535] Data processing: Creating and sending prompts to generative AI models.

[0536] Output: A radio show script generated by the generative AI model.

[0537] For example, the prompt:

[0538] User name: Yamada Taro

[0539] Interesting news categories: Business, Technology

[0540] Daily schedule: Meeting at 8am

[0541] Prompt statement:

[0542] "Generate a morning news radio show for user Taro Yamada. The categories are business and technology, and the schedule includes a meeting at 8am."

[0543] Step 4: Convert to audio data

[0544] Server: The generated radio program script is converted into voice data using a TTS (Text-To-Speech) engine.

[0545] Input: A generated radio script.

[0546] Data processing: Voice data generation using a TTS engine.

[0547] Output: The generated audio data.

[0548] Step 5: Streaming audio data

[0549] Server: Sends the generated voice data to the user's device.

[0550] Input: The generated audio data.

[0551] Data processing: Preparing and sending audio data for distribution.

[0552] Output: The audio data sent to the device.

[0553] Device: Receives audio data and prepares it for playback, allowing users to listen to radio-style audio content through the app.

[0554] Input: Audio data received from the server.

[0555] Data processing: preparing for playback (e.g., caching, storing in memory).

[0556] Output: The audio content that is played to the user.

[0557] Step 6: Collect and analyze feedback

[0558] Users: After listening to the audio content, they provide feedback and ratings within the app.

[0559] Input: User input, such as ratings and feedback.

[0560] Output: Feedback typed into the terminal.

[0561] Terminal: Sends the entered feedback to the server.

[0562] Input: User feedback.

[0563] Data processing: packaging and sending feedback.

[0564] Output: Feedback sent to the server.

[0565] Server: Stores the feedback information in a database and analyzes it. Based on the analysis results, the system's behavior and content generation process are improved.

[0566] Input: Feedback sent from the device.

[0567] Data processing: Analysis of feedback and storage in a database.

[0568] Output: Improvements to system behavior and content generation processes.

[0569] (Application example 1)

[0570] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0571] Conventional voice information systems require users to manually search for information, which reduces the efficiency of information gathering and use. There are also concerns about the negative health effects of using a smartphone while sleeping. Furthermore, there is a lack of personalized information provision tailored to individual user needs, creating a need for improved user experience.

[0572] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0573] In this invention, the server includes a means for generating prompt sentences for generating and delivering voice information, a means for utilizing a generative AI model for providing the voice information, and a means for adjusting the output content of the generative AI model using the results of the behavior analysis, thereby enabling efficient and personalized voice information delivery according to the user's needs.

[0574] "Generative means" is the ability to create new information or content for a specific purpose.

[0575] "Means of collecting information" refers to the function of obtaining necessary data and news from external sources.

[0576] "Means for automatic generation" refers to the ability of the system to autonomously create content without the need for human intervention.

[0577] "Means for converting into voice" refers to technology for converting text data into voice data.

[0578] "Means of distribution" refers to the function of delivering the generated voice data and information to the user's device.

[0579] "Means for generating prompt sentences for generating and delivering voice information" refers to a function that automatically generates initial input (prompts) for the generative AI model to create personalized voice information.

[0580] A "server" is a computer system that processes requested information and manages data.

[0581] "Means for saving and analyzing user information" refers to the function of saving user interests and schedule information in a database and analyzing it.

[0582] "Means of collecting information from external sources" refers to the ability to obtain necessary news and weather information from external APIs and databases.

[0583] "Means for editing the generated script" refers to a function for manually or automatically correcting and adjusting the generated content as needed.

[0584] "Means for transmitting voice data to the user's terminal" refers to a function for delivering the generated voice data to the user's smartphone or other device.

[0585] "Means of using a generative AI model to provide voice information" refers to technology that uses generative AI to generate voice information appropriate for the user.

[0586] "Means for collecting and storing user feedback" refers to a function that obtains user ratings and opinions and stores them in a database.

[0587] "Means for analyzing feedback and improving the overall operation of the system" refers to a function for analyzing collected feedback to improve system performance and user satisfaction.

[0588] "Means for adjusting the output content of the generative AI model using the results of behavior analysis" refers to a function that optimizes the parameters and output of the generative AI based on the analysis results.

[0589] This invention relates to a voice information providing system that allows users to efficiently obtain necessary information and prevent "smartphone use while sleeping." This system is realized by combining the following main functions.

[0590] First, the server collects user interest and schedule information, stores it in a database, and analyzes it. Users launch the radio app on their smartphone and input their news categories of interest (e.g., sports, entertainment, business, etc.) and daily schedule information. This identifies the user's individual needs.

[0591] The server then sends requests to external news and weather APIs to gather the latest news articles and weather information, which is then filtered based on the user's interests.

[0592] Based on the collected information, the server uses a generative AI model to automatically generate a personalized radio show script suitable for the user. The script is created by inputting the generative AI model using prompt sentences such as the following:

[0593] "User is interested in sports and entertainment. Generate a personalized newscast script with the latest news and this morning's schedule information."

[0594] The generated script is converted into audio data using a server-based text-to-speech (TTS) engine. In this case, we use Google Cloud Text-to-Speech.

[0595] The generated audio data is then sent from the server to the user's device, where it is prepared for playback by the smartphone app, allowing the user to listen to personalized radio-style audio content through the app.

[0596] Furthermore, after listening to the audio content, users can enter feedback and ratings within the app. The device then sends this feedback to the server, which then stores the feedback information in a database for analysis. The results of this analysis are used to adjust the generative AI model and improve the overall system's operation.

[0597] For example, when a user wakes up in the morning and launches the radio app on their smartphone, an automatically generated radio program will play along with a friendly message like, "Good morning, user." The server generates the script for this radio program based on the latest news, weather information, and the user's schedule (e.g., work meetings), allowing the user to efficiently obtain the information they need without having to look at their smartphone screen.

[0598] This system prevents users from using their smartphones while sleeping and allows them to efficiently obtain the information they need.

[0599] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0600] Step 1:

[0601] Collecting user information

[0602] A user opens a radio app on their smartphone and enters the news categories they are interested in (sports, entertainment, business, etc.) and their daily schedule information. This information is input data and is important for identifying the user's individual needs. This information is sent to a server for subsequent information collection and analysis.

[0603] Step 2:

[0604] Saving and analyzing user information

[0605] The server stores the information entered by the user (such as name, interests, schedule, etc.) in a database. This information is then analyzed and output to identify user interests and behavioral patterns. The results of this analysis are used in the next news gathering process.

[0606] Step 3:

[0607] Gathering external information

[0608] The server sends requests to external news and weather APIs to retrieve the latest news articles and weather information. This is the input data. The collected information is filtered based on the user's interests and stored in a database as personalized information. This is the output data.

[0609] Step 4:

[0610] Automatic generation of radio program scripts

[0611] The server automatically generates a radio show script using a generative AI model based on the saved user information and collected external information. Specifically, it inputs the following prompt sentences into the generative AI model (e.g., GPT-3):

[0612] "User is interested in sports and entertainment. Generate a personalized newscast script with the latest news and this morning's schedule information."

[0613] The generated script becomes the output data.

[0614] Step 5:

[0615] Script audio conversion

[0616] The server converts the generated radio program script into audio data using a TTS (Text-To-Speech) engine (e.g., Google Cloud Text-to-Speech). The input data is the generated script, and the output data is audio data. The audio data is optimized for user listening.

[0617] Step 6:

[0618] Audio data distribution

[0619] The server sends the audio data to the user's device. The device receives the audio data and prepares it for playback. The user can listen to personalized radio programs through the radio app. The delivery of the audio data is the output data.

[0620] Step 7:

[0621] Gathering feedback

[0622] After listening to the audio content, users enter their feedback and ratings within the app. This is the input data. This feedback is sent from the device to the server and stored in the database. This is the output data.

[0623] Step 8:

[0624] Analyzing feedback and improving the system

[0625] The server analyzes the collected feedback and adjusts the output of the generative AI model based on the results. This improves the overall operation of the system and enables the provision of voice information that better meets the user's needs. The analyzed feedback data is the output data.

[0626] The above are the specific processing steps of the system, which is a mechanism for efficiently providing personalized voice information to users.

[0627] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0628] The present invention relates to a voice information provision system that allows users to efficiently obtain necessary information and prevents them from using their smartphones while sleeping. The system includes a generating means, a collecting means, an automatic generating means, a converting means to voice, a distributing means, a means for storing and analyzing user information, a means for collecting information from external sources, a means for editing the generated script, a means for transmitting voice data to the user's device, a means for collecting and storing user feedback, a means for analyzing the feedback and improving the overall operation of the system, and an emotion engine for recognizing user emotions.

[0629] 1. Entering and saving user information

[0630] User: Launches the radio app and accesses the account registration or login screen. Enters the news category of interest (sports, entertainment, business, etc.), daily schedule information, name, email address, and password.

[0631] Terminal: Sends the information entered by the user (name, email address, password, news category, schedule information) to the server.

[0632] Server: Stores and analyzes user information in a database. Updates user profiles based on interests and schedule information.

[0633] 2. Collection of information

[0634] Server: Sends requests to external news and weather APIs to collect the latest news articles and weather information.

[0635] 3. Automatic Generation of Radio Programs

[0636] Server: Using AI generated from saved user interest and schedule information and past viewing history, the server automatically generates radio program scripts suited to the user.

[0637] 4. Convert to audio data

[0638] Server: The generated radio program script is converted into voice data using a TTS (Text-To-Speech) engine.

[0639] 5. Audio data distribution

[0640] Server: Sends the generated voice data to the user's device.

[0641] Device: Prepares the received audio data for playback, allowing users to listen to radio-style audio content through the app.

[0642] 6. Emotion Recognition by Emotion Engine

[0643] User: By providing voice input through the microphone while using the Radio app at designated times and events.

[0644] Device: Sends the user's voice input to the server.

[0645] Server: Using the emotion engine, recognize emotions from the user's voice input. The recognized emotions are stored in a database and reflected in the user profile.

[0646] 7. Adjust your script based on emotion

[0647] Server: Based on the user's emotional information, the generative AI adjusts the content of the radio program script. For example, if the user is feeling stressed, it will adjust the script to include more relaxing topics and music.

[0648] 8. Feedback Collection and Analysis

[0649] Users: After listening to the audio content, they provide feedback and ratings within the app.

[0650] Terminal: Sends the entered feedback to the server.

[0651] Server: Feedback information is stored in a database and analyzed to improve the system's operation and the script generation process.

[0652] For example, when a user wakes up in the morning, they launch a radio app on their smartphone. The device starts playing an automatically generated radio program along with a friendly message like "Good morning, user." The server generates a script for this radio program based on the latest news, weather information, and the user's schedule (e.g., work meetings). Furthermore, the emotion engine recognizes the user's emotions through their voice input and adjusts the script content based on those emotions. By listening to this, users can efficiently obtain the information they need without having to look at their smartphone screen.

[0653] This system prevents users from using their smartphones while sleeping and allows them to efficiently obtain the information they need. It also provides a more personalized experience by providing content that matches the user's emotions with an emotion engine.

[0654] The processing flow will be explained below.

[0655] Step 1:

[0656] User: Launches the radio app and accesses the account registration or login screen. Enters the news category of interest (sports, entertainment, business, etc.), daily schedule information, name, email address, and password.

[0657] Step 2:

[0658] Terminal: Sends information entered by the user to the server, including name, email address, password, news category, and schedule information.

[0659] Step 3:

[0660] Server: Stores and analyzes user information in a database. Updates user profiles based on interests and schedule information.

[0661] Step 4:

[0662] Server: Sends requests to external news and weather APIs to collect the latest news articles and weather information.

[0663] Step 5:

[0664] Server: Using AI technology to automatically generate radio program scripts tailored to each user based on their saved interests, schedule, and past listening history. The scripts include greeting messages, the latest news, weather information, and schedule reminders.

[0665] Step 6:

[0666] Server: The generated radio program script is converted into voice data using a TTS (Text-To-Speech) engine.

[0667] Step 7:

[0668] Server: Sends the generated voice data to the user's device.

[0669] Step 8:

[0670] Device: Prepares the received audio data for playback, allowing users to listen to radio-style audio content through the app.

[0671] Step 9:

[0672] User: By providing voice input through the microphone while using the Radio app at designated times and events.

[0673] Step 10:

[0674] Device: Sends the user's voice input to the server.

[0675] Step 11:

[0676] Server: Using the emotion engine, recognize emotions from the user's voice input. The recognized emotions are stored in a database and reflected in the user profile.

[0677] Step 12:

[0678] Server: Based on the user's emotional information, the generative AI adjusts the content of the radio program script. For example, if the user is feeling stressed, it will adjust the script to include more relaxing topics and music.

[0679] Step 13:

[0680] Terminal: Receives the voice data generated based on the contents of the readjusted script.

[0681] Step 14:

[0682] Device: Prepares for playback and allows the user to listen to tailored radio-style audio content.

[0683] Step 15:

[0684] Users: After listening to the audio content, they provide feedback and ratings within the app.

[0685] Step 16:

[0686] Terminal: Sends the entered feedback to the server.

[0687] Step 17:

[0688] Server: Feedback information is stored in a database and analyzed to improve the system's operation and the script generation process.

[0689] Example 2

[0690] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0691] In today's information society, users need ways to efficiently obtain the information they need. However, many users have the habit of staring at their smartphone screens for long periods of time, which can lead to health problems such as decreased eyesight and poor posture. Furthermore, there is a lack of personalized information delivery systems that match the interests and emotions of individual users. Therefore, there is a need for a system that can provide information tailored to each user's needs, prevent smartphone use while sleeping, and reduce the impact on health.

[0692] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a generation means, an information collection means, an automatic generation means, a voice conversion means, and a distribution means. This allows the user to efficiently obtain the necessary information without using their eyes. In addition, since the server includes an emotion recognition means that recognizes the user's emotion and a script adjustment means that adjusts the script content based on the recognized emotion, it is possible to provide personalized information and increase user satisfaction.

[0693] A "generation means" is a device or process that has the function of creating data or content based on specified information.

[0694] An "information gathering tool" is a device or process that obtains the required data from an external source.

[0695] An "automatic generation means" is a device or process that has the ability to automatically generate content using artificial intelligence or algorithms based on collected data and user information.

[0696] "Speech conversion means" means a device or process that converts generated text data into speech data, such as a text-to-speech (TTS) engine.

[0697] A "delivery mechanism" is a device or process that transmits generated or converted audio data to a user's device.

[0698] "User information storage means" refers to a device or process that has the function of storing information provided by a user in a database or the like.

[0699] An "external information gathering means" is a device or process that obtains the latest news, weather information, etc. from external sources.

[0700] "Script editing means" refers to a device or process that has the function of editing and adjusting the generated script based on the user's needs and feelings.

[0701] "Audio data transmission means" is a device or process capable of transmitting generated audio data to a user's device.

[0702] A "user feedback collection means" is a device or process that has the function of collecting user ratings and opinions.

[0703] "Feedback analysis means" refers to a device or process that has the function of analyzing collected user feedback and using it to improve the system.

[0704] "Emotion recognition means" refers to a device or process that has the function of determining emotions from user voice input, etc.

[0705] A "script adjustment means" is a device or process that has the function of adjusting the script content of a radio program based on the recognized emotional information.

[0706] The present invention relates to a voice information provision system that allows users to efficiently obtain necessary information and prevents "smartphone use while sleeping." The system includes a generation unit, an information collection unit, an automatic generation unit, a voice conversion unit, and a distribution unit. It also includes a user information storage unit, an external information collection unit, a script editing unit, a voice data transmission unit, a user feedback collection unit, a feedback analysis unit, an emotion recognition unit, and a script adjustment unit.

[0707] First, the information provided by the user is sent from the device to a server. The server stores this information in a database and updates the user profile. For example, a user enters their name, email address, news categories of interest, and schedule information into a radio app. This information is sent from the device to the server, which stores it in a database such as MySQL and analyzes it.

[0708] The server then sends requests to external news or weather APIs to gather the latest news articles or weather information. For example, an HTTP GET request can be used to retrieve the latest articles from an external news API.

[0709] The server inputs prompts into the AI ​​model based on the saved user information, past viewing history, and external information, and automatically generates a radio program script. For example, the prompt could be: "Generate a radio program script that includes the latest news and weather forecast based on the user's interests."

[0710] The generated script is converted into voice data using a TTS (Text-To-Speech) engine in a voice conversion means on the server, for example, by using the Google Text-to-Speech API.

[0711] The server then delivers the audio data to the user's device. The audio data file is sent via an HTTP response, and the device receives the audio data, prepares it for playback, and starts playback using the media player API.

[0712] Furthermore, when a user uses the radio app at a specified time or event and inputs voice data through the microphone, the device sends this voice data to the server. The server uses emotion recognition to recognize emotions from the user's voice input, stores them in a database, and reflects them in the user profile. Based on the recognized emotion information, it inputs prompts to the generative AI model, such as "The user is feeling stressed, so please adjust the script to include relaxing topics and music." This allows the script content to be adjusted appropriately.

[0713] Finally, after listening to the audio content, the user can provide feedback and ratings, which are then sent to the server, which stores the feedback information in a database and analyzes it to improve the system's operation and script generation process.

[0714] For example, when a user wakes up in the morning and launches a radio app on their smartphone, an automatically generated radio program is played along with a friendly message such as "Good morning, user." The program includes information such as "Today's weather is sunny. The temperature is 20 degrees, with a maximum temperature of 25 degrees. Also, there is a meeting at 3 pm today, so don't forget to get ready." When the user asks, "What do you think about today's news?", the system recognizes the user's emotions and provides more relaxing topics based on the results.

[0715] Example prompt sentence:

[0716] "Generate radio show scripts with breaking news and weather forecasts based on user interests."

[0717] In this way, users can efficiently obtain the information they need without looking at their smartphone screen, and can receive information that is tailored to their emotions.

[0718] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0719] Step 1:

[0720] The user launches the radio app and accesses the account registration screen or login screen. The user enters their name, email address, password, and news categories of interest (daily schedule information). This is the input information. The device sends the information entered by the user to the server. Specifically, it uses the REST API to send an HTTP POST request. At this time, the input data is the name, email address, password, news categories, and schedule information, and the output is an HTTP request containing this information.

[0721] Step 2:

[0722] The server stores the received user information in a database. Specifically, it uses a database such as MySQL to store the data using an INSERT query. It then updates the user profile based on this information. In this process, the input data is the user information sent from the device, and the output is the stored data and the updated user profile.

[0723] Step 3:

[0724] The server sends HTTP GET requests to external news APIs and weather information APIs to collect the latest news articles and weather information. The input data is the API request, and the output is the retrieved news articles and weather forecast data. This data is then analyzed within the server to extract the necessary information.

[0725] Step 4:

[0726] The server creates and inputs a prompt to the generative AI model based on user information, past viewing history, external information, etc. For example, the prompt might be, "Generate a radio program script that includes the latest news and weather forecast based on the user's interests." The input data is the user information and the prompt, and the output is the generated radio program script.

[0727] Step 5:

[0728] The server inputs the generated radio program script into a TTS (Text-To-Speech) engine and converts it into voice data. As a concrete example, we will use the Google Text-to-Speech API. The input data is the generated script, and the output is voice data generated by the TTS engine.

[0729] Step 6:

[0730] The server sends the generated audio data to the user's device. For example, it sends an audio data file as an HTTP response, and the device receives the audio data and prepares for playback. Specifically, it starts playback using a media player API. The input data is the audio data, and the output is the audio that is received and played.

[0731] Step 7:

[0732] The user uses the radio app at a designated time or event and inputs voice through the microphone. The device sends this voice input data to the server. The input data is the user's voice, and the output is the voice input data sent to the server.

[0733] Step 8:

[0734] The server uses emotion recognition means to recognize emotions from the user's voice input. For example, using an emotion analysis API, it obtains the result "The user is relaxed." The input data is the voice input data, and the output is the analyzed emotion information. This is saved in the database and reflected in the user profile.

[0735] Step 9:

[0736] The server inputs prompts to the generative AI model based on the recognized emotional information. For example, it might say, "The user is feeling stressed, so please adjust the prompts to include relaxing topics and music." The input data are the recognized emotional information and prompts, and the output is an adjusted radio program script.

[0737] Step 10:

[0738] After listening to the audio content, the user inputs feedback and ratings within the app. The device sends this feedback to the server. The input data is the feedback, and the output is the feedback data sent to the server.

[0739] Step 11:

[0740] The server stores the feedback information in a database and analyzes it, which improves the system's behavior and the generation process. The input data is the feedback information, and the output is the analysis results and a list of improvements.

[0741] This is the specific processing flow of this system. This series of steps allows users to efficiently obtain the information they need without using their vision, and also provides them with personalized information that matches their emotions.

[0742] (Application example 2)

[0743] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0744] In modern society, many people operate smart devices while lying down, which often leads to poor sleep quality and health problems. Furthermore, it is difficult to efficiently obtain necessary information, which contributes to stress in daily life. The purpose of this invention is to solve these problems and support a healthy lifestyle while enabling users to efficiently obtain necessary information.

[0745] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting and saving user information, means for collecting information from external information sources, means for automatically generating a radio program script based on the user's interests and schedule information, means for converting the generated script into audio data, means for distributing the audio data, means for recognizing emotions from the user's voice input, means for adjusting the script content based on the recognized emotions, and means for collecting and analyzing user feedback. This allows users to efficiently obtain necessary information without looking at the screen of their smart device, preventing them from using their smartphone while sleeping. Furthermore, providing personalized content based on emotions is expected to reduce stress and improve quality of life.

[0746] "Means for inputting and storing user information" refers to the means by which a user inputs information about their interests and schedule and stores it in a database.

[0747] "Means of collecting information from external sources" refers to means of collecting the latest information using APIs, etc., to obtain external news and weather information.

[0748] "Means for automatically generating radio program scripts based on user interests and schedule information" means means for a generative AI model to use user profile data to create radio program scripts that are appropriate for the user.

[0749] The "means for converting the generated script into voice data" refers to a means for converting the generated script in text form into voice data using a TTS (Text-To-Speech) engine.

[0750] "Means for distributing audio data" refers to means for transmitting the generated audio data to a user's smartphone or other device and distributing audio content.

[0751] The "means for recognizing emotions from user voice input" refers to a means for analyzing emotions from the user's voice using an emotion engine and acquiring emotion data.

[0752] "Means for adjusting script content based on recognized emotions" refers to a means by which the generative AI model dynamically changes the script content of a radio program based on the acquired emotional data.

[0753] "Means for collecting and analyzing user feedback" refers to the means for storing the ratings and opinions provided by users in a database and analyzing them to help improve the system.

[0754] This invention provides a voice information provision system that allows users to efficiently obtain necessary information and prevents excessive use of smart devices. The system generates personalized voice content based on the user's interests and schedule information, and adjusts the content by recognizing the user's emotions.

[0755] Hardware and Software Used

[0756] The system of the present invention uses a server, user devices (smartphones, tablets, etc.), and various APIs (news API, weather information API, etc.). The server performs the main processing and performs various data processing and calculations using advanced software tools such as generative AI models, TTS (Text-To-Speech) engines, and emotion recognition engines.

[0757] Processing flow

[0758] 1. User information input and storage:

[0759] The server stores the name, email address, interest categories, schedule information, etc. that the user entered when registering an account in a database. This information is analyzed by the server and reflected in the user profile.

[0760] 2. Collection of Information:

[0761] The server sends requests to external news and weather APIs to collect the latest news articles and weather information in real time.

[0762] 3. Automatic generation of radio program scripts:

[0763] Based on the collected information and the user's profile, the server uses a generative AI model to automatically generate a radio program script suitable for the user, including news related to the user's interests and necessary schedule information.

[0764] 4. Conversion to audio data:

[0765] The server converts the generated script into audio data using a TTS engine, which can be heard by the user without any visual intervention.

[0766] 5. Audio data delivery:

[0767] The server transmits the generated voice data to the user's terminal, and the terminal plays back the received voice data.

[0768] 6. Emotion recognition:

[0769] When a user makes a voice input, the device sends the voice data to the server, which uses an emotion engine to recognize the user's emotion from the voice data and stores the information in a database.

[0770] 7. Content adjustment based on emotions:

[0771] The server uses the generative AI model to adjust the radio program script based on the recognized emotion data, for example, by including more relaxing topics and music if the user is feeling stressed.

[0772] 8. Feedback Collection and Analysis:

[0773] After listening to the audio content, users can input feedback, which is then sent to the server, which then stores the collected feedback in a database and analyzes it to improve the overall operation of the system.

[0774] Examples and prompts

[0775] As a concrete example, the following shows a specific case where a news API and sentiment model are utilized.

[0776] 1. News gathering examples:

[0777] Send a request to the URL https: / / newsapi.org / v2 / top-headlines?country=jp&category=technology&apiKey=your_news_api_key to get the latest technology news.

[0778] 2. Example prompt sentences for emotion recognition model:

[0779] In response to a user's voice input of "How's the weather today?", the emotion recognition engine generates a script to reply, "The weather is sunny today. It looks like you'll have a pleasant time."

[0780] Through these steps, the system of the present invention can efficiently provide necessary information to users while promoting healthy device use.

[0781] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0782] Step 1:

[0783] A user uses a smart device to provide input information (name, email address, password, interest categories, schedule information) on an account registration screen or login screen. The device sends this input information to a server. The server stores the received user information in a database and analyzes the information to build a user profile. The input is the user information, and the output is the user profile stored in the database.

[0784] Step 2:

[0785] The server periodically sends requests to external APIs (such as news APIs and weather APIs) to collect the latest information based on the user's interests. This collected data is used to generate personalized information based on the user profile. The input is news and weather data retrieved from the APIs, and the output is the latest information stored on the server.

[0786] Step 3:

[0787] The server automatically generates radio show scripts using a generative AI model based on user interests and schedule information, including incorporating collected news and weather information and processing the data to reflect user interests. The inputs are the user profile and collected external data, and the output is the generated radio show script.

[0788] Step 4:

[0789] The server converts the generated radio program script into voice data using a TTS (Text-To-Speech) engine, which generates natural-sounding voice from the text data. The input is the generated script text, and the output is the generated voice data.

[0790] Step 5:

[0791] The server sends the generated audio data to the user's device. The device prepares the received audio data for playback, allowing the user to listen to the audio content through the app. The input is the generated audio data, and the output is the audio data sent to the user's device.

[0792] Step 6:

[0793] While listening to audio content, a user provides emotional information through voice input. The device sends this voice data to a server, which then uses an emotion engine to recognize the user's emotion and stores the information in a database. The input is the user's voice input, and the output is the recognized emotional data.

[0794] Step 7:

[0795] The server uses the recognized emotion data to tailor the radio show script using a generative AI model. For example, if the user's stress level is high, the server might include more relaxing topics and music. The input is the recognized emotion data, and the output is the tailored radio show script.

[0796] Step 8:

[0797] After listening to the audio content, the user inputs feedback. The terminal sends this feedback information to the server, which then stores the collected feedback in a database and analyzes it to improve the system's operation and the script generation process. The input is the user's feedback, and the output is the feedback information stored in the database and its analysis results.

[0798] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0799] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0800] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0801] [Third embodiment]

[0802] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0803] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0804] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0805] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0806] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0807] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0808] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0809] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0810] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0811] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0812] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0813] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0814] The present invention relates to a voice information provision system that allows users to efficiently obtain necessary information and prevents them from using their smartphones while sleeping. The system includes a generating means, a collecting means, an automatic generating means, a converting means to voice, a distributing means, a means for storing and analyzing user information, a means for collecting information from external sources, a means for editing the generated script, a means for transmitting voice data to the user's device, a means for collecting and storing user feedback, and a means for analyzing the feedback and improving the operation of the entire system.

[0815] 1. Entering and saving user information

[0816] User: Launches the radio app and accesses the account registration or login screen. Enters the news categories of interest (sports, entertainment, business, etc.) and daily schedule information.

[0817] Device: Sends information entered by the user (such as name, email address, and password), as well as interests and schedule information, to the server.

[0818] Server: Stores user information in a database and analyzes it.

[0819] 2. Collection of information

[0820] Server: Sends requests to external news and weather APIs to collect the latest news articles and weather information.

[0821] 3. Automatic Generation of Radio Programs

[0822] Server: Based on the user's saved interest and schedule information and past viewing history, generative AI is used to automatically generate radio program scripts suitable for the user.

[0823] 4. Convert to audio data

[0824] Server: The generated radio program script is converted into voice data using a TTS (Text-To-Speech) engine.

[0825] 5. Audio data distribution

[0826] Server: Sends the generated voice data to the user's device.

[0827] Device: Prepares the received audio data for playback, allowing users to listen to radio-style audio content through the app.

[0828] 6. Feedback Collection and Analysis

[0829] Users: After listening to the audio content, they provide feedback and ratings within the app.

[0830] Terminal: Sends the entered feedback to the server.

[0831] Server: Feedback information is stored in a database and analyzed to improve the system's operation and the script generation process.

[0832] For example, when a user wakes up in the morning, they launch a radio app on their smartphone. The device starts playing an automatically generated radio program along with a friendly message like "Good morning, user." The server generates the script for this radio program based on the latest news, weather information, and the user's schedule (e.g., work meetings). By listening to this, the user can efficiently obtain the information they need without having to look at their smartphone screen.

[0833] This system prevents users from using their smartphones while sleeping and allows them to efficiently obtain the information they need.

[0834] The processing flow will be explained below.

[0835] Step 1:

[0836] User: Launches the radio app and accesses the account registration or login screen. Enters the news category of interest (sports, entertainment, business, etc.), daily schedule information, name, email address, and password.

[0837] Step 2:

[0838] Terminal: Sends information entered by the user to the server, including name, email address, password, news category, and schedule information.

[0839] Step 3:

[0840] Server: Stores and analyzes user information in a database. Updates user profiles based on interests and schedule information.

[0841] Step 4:

[0842] Server: Sends requests to external news and weather APIs to collect the latest news articles and weather information.

[0843] Step 5:

[0844] Server: Using AI technology, the server automatically generates radio program scripts tailored to each user based on their saved interests, schedule, and past listening history. The scripts include greeting messages, the latest news, weather information, and schedule reminders.

[0845] Step 6:

[0846] Server: The generated radio program script is converted into voice data using a TTS (Text-To-Speech) engine.

[0847] Step 7:

[0848] Server: Sends the generated voice data to the user's device.

[0849] Step 8:

[0850] Device: Prepares to play the received audio data, allowing users to listen to radio-style audio content through the app.

[0851] Step 9:

[0852] Users: After listening to the audio content, they provide feedback and ratings within the app.

[0853] Step 10:

[0854] Terminal: Sends the entered feedback to the server.

[0855] Step 11:

[0856] Server: Feedback information is stored in a database and analyzed to improve the system's operation and the script generation process.

[0857] Example 1

[0858] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0859] In modern society, many users use smartphones to gather information, but in certain situations (e.g., using a smartphone while lying down), it can be difficult to see the screen. This situation can have a negative impact on users' lifestyles and health. Furthermore, it can be difficult to select and efficiently gather information, making it difficult for users to quickly obtain the information they need.

[0860] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0861] In this invention, the server includes means for saving and analyzing information entered by the user, means for collecting data from external information sources, means for generating a script based on the collected data, means for converting the generated script into audio data, and means for delivering the audio data, thereby enabling the user to efficiently obtain necessary information by voice without looking at the screen.

[0862] "Means for storing and analyzing information entered by users" refers to a device or system that stores data entered by users, such as personal information, interests, and schedules, analyzes that data, and uses it to generate appropriate content.

[0863] A "means for collecting data from external sources" is a device or system that collects up-to-date information from external data sources such as news APIs or weather APIs.

[0864] "Means for generating scripts based on collected data" refers to a device or system that automatically creates appropriate radio program scripts for users using a generative AI model based on collected news, weather information, etc.

[0865] The "means for converting the generated script into voice data" refers to a device or system that converts the generated text-format script into voice data using a TTS (Text-to-Speech) engine.

[0866] "Means for distributing audio data" refers to a device or system that transmits the converted audio data to the user's terminal so that it can be played back.

[0867] "Means for editing a generated script" refers to a device or system that manually or automatically modifies and edits an automatically generated script.

[0868] "Feedback collection and storage means" means a device or system that collects and stores user ratings and opinions within the app.

[0869] A "means for analyzing feedback and improving overall system operation" is a device or system that analyzes collected feedback information and optimizes system operation or the content generation process based on that information.

[0870] "Server" refers to a central processing unit or the entire system for executing and managing all of the above means.

[0871] The present invention is a voice information provision system that allows users to efficiently obtain necessary information and prevents them from using their smartphones while sleeping. This system includes processes from user information input to voice data delivery and even feedback collection and analysis. Specific embodiments of the system are described below.

[0872] Feature Overview

[0873] 1. Entering and saving user information

[0874] User: Using a device such as a smartphone or tablet, the user launches a radio app and accesses the account registration or login screen, where they enter their name, email address, password, or the news category of their interest (e.g., sports, entertainment, business), as well as their daily schedule information.

[0875] Terminal: Validates the information entered by the user to ensure it is in the correct format, then sends this information to the server.

[0876] Server: Receives the transmitted information and stores it in a database. The stored information is used in the next process.

[0877] 2. Collection of information

[0878] Server: Sends requests to external news APIs (e.g., Google News API) or weather APIs (e.g., OpenWeatherMap API) and collects the necessary data.

[0879] 3. Automatic Generation of Radio Programs

[0880] Server: Based on the collected data, a generative AI model (e.g., OpenAI GPT-4) is used to automatically generate a radio program script. The following are examples of prompts for the AI ​​model:

[0881] User name: Yamada Taro

[0882] Interesting news categories: Business, Technology

[0883] Daily schedule: Meeting at 8am

[0884] Prompt statement:

[0885] "Generate a morning news radio show for user Taro Yamada. The categories are business and technology, and the schedule includes a meeting at 8am."

[0886] 4. Convert to audio data

[0887] Server: The generated radio program script is converted into audio data using a TTS (Text-To-Speech) engine (e.g., Google Text-to-Speech API).

[0888] 5. Audio data distribution

[0889] Server: Sends the generated voice data to the user's device.

[0890] Device: Receives audio data, prepares it for playback, and allows users to listen to radio-style audio content through the app.

[0891] 6. Feedback Collection and Analysis

[0892] Users: After listening to the audio content, they provide feedback and ratings within the app.

[0893] Terminal: Sends the entered feedback to the server.

[0894] Server: Stores the feedback information in a database and analyzes it. Based on the analysis results, the overall system behavior and content generation process are improved.

[0895] Specific examples

[0896] When a user wakes up in the morning, they launch the radio app on their smartphone. The device starts playing an automatically generated radio program along with a friendly message like "Good morning, user." The server generates the script for this radio program based on the latest news, weather information, and the user's schedule (e.g., work meetings). By listening to this, users can efficiently obtain the information they need without looking at their smartphone screen. This system prevents users from "using their smartphone while sleeping" and allows them to efficiently obtain the information they need.

[0897] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0898] System processing steps

[0899] Step 1: Enter and save user information

[0900] User: Launches a radio app using a smartphone or tablet device, accesses the account registration or login screen, and enters their name, email address, password, news categories of interest (e.g., sports, entertainment, business), and daily schedule information.

[0901] Input: Personal information, interests, and schedule information entered by the user.

[0902] Output: Information entered into the terminal is saved.

[0903] Terminal: Validates the information entered by the user to ensure it is in the correct format, and after successful validation, sends the information to the server.

[0904] Input: Information entered by the user.

[0905] Data processing: Input validation (e.g., checking email address format, password strength).

[0906] Output: Information ready to be sent to the server.

[0907] Server: Receives the information sent from the device and stores it in a database, which makes the data available for subsequent processing.

[0908] Input: User information sent from the device.

[0909] Data processing: Data storage.

[0910] Output: User information stored in the database.

[0911] Step 2: Gather information

[0912] Server: Sends requests to external news and weather APIs to collect the latest news articles and weather information.

[0913] Input: Information sent in the API request (user interest categories and region information).

[0914] Data processing: Generating and sending API requests.

[0915] Output: Collected news articles and weather information.

[0916] Server: Analyzes the collected information and stores it in a database in the form of news titles, summaries, weather forecasts, etc.

[0917] Input: Collected news articles and weather information.

[0918] Data processing: Analyzing data and organizing them into categories.

[0919] Output: Information stored in a database after analysis.

[0920] Step 3: Automatic generation of radio programs

[0921] Server: Automatically generates radio program scripts using a generative AI model based on user information in the database and collected news and weather information.

[0922] Input: User interests, news, and weather information stored in a database.

[0923] Data processing: Creating and sending prompts to generative AI models.

[0924] Output: A radio show script generated by the generative AI model.

[0925] For example, the prompt:

[0926] User name: Yamada Taro

[0927] Interesting news categories: Business, Technology

[0928] Daily schedule: Meeting at 8am

[0929] Prompt statement:

[0930] "Generate a morning news radio show for user Taro Yamada. The categories are business and technology, and the schedule includes a meeting at 8am."

[0931] Step 4: Convert to audio data

[0932] Server: The generated radio program script is converted into voice data using a TTS (Text-To-Speech) engine.

[0933] Input: A generated radio script.

[0934] Data processing: Voice data generation using a TTS engine.

[0935] Output: The generated audio data.

[0936] Step 5: Streaming audio data

[0937] Server: Sends the generated voice data to the user's device.

[0938] Input: The generated audio data.

[0939] Data processing: Preparing and sending audio data for distribution.

[0940] Output: The audio data sent to the device.

[0941] Device: Receives audio data and prepares it for playback, allowing users to listen to radio-style audio content through the app.

[0942] Input: Audio data received from the server.

[0943] Data processing: preparing for playback (e.g., caching, storing in memory).

[0944] Output: The audio content that is played to the user.

[0945] Step 6: Collect and analyze feedback

[0946] Users: After listening to the audio content, they provide feedback and ratings within the app.

[0947] Input: User input, such as ratings and feedback.

[0948] Output: Feedback typed into the terminal.

[0949] Terminal: Sends the entered feedback to the server.

[0950] Input: User feedback.

[0951] Data processing: packaging and sending feedback.

[0952] Output: Feedback sent to the server.

[0953] Server: Stores the feedback information in a database and analyzes it. Based on the analysis results, the system's behavior and content generation process are improved.

[0954] Input: Feedback sent from the device.

[0955] Data processing: Analysis of feedback and storage in a database.

[0956] Output: Improvements to system behavior and content generation processes.

[0957] (Application example 1)

[0958] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0959] Conventional voice information systems require users to manually search for information, which reduces the efficiency of information gathering and use. There are also concerns about the negative health effects of using a smartphone while sleeping. Furthermore, there is a lack of personalized information provision tailored to individual user needs, creating a need for improved user experience.

[0960] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0961] In this invention, the server includes a means for generating prompt sentences for generating and delivering voice information, a means for utilizing a generative AI model for providing the voice information, and a means for adjusting the output content of the generative AI model using the results of the behavior analysis, thereby enabling efficient and personalized voice information delivery according to the user's needs.

[0962] "Generative means" is the ability to create new information or content for a specific purpose.

[0963] "Means of collecting information" refers to the function of obtaining necessary data and news from external sources.

[0964] "Means for automatic generation" refers to the ability of the system to autonomously create content without the need for human intervention.

[0965] "Means for converting into voice" refers to technology for converting text data into voice data.

[0966] "Means of distribution" refers to the function of delivering the generated voice data and information to the user's device.

[0967] "Means for generating prompt sentences for generating and delivering voice information" refers to a function that automatically generates initial input (prompts) for the generative AI model to create personalized voice information.

[0968] A "server" is a computer system that processes requested information and manages data.

[0969] "Means for saving and analyzing user information" refers to the function of saving user interests and schedule information in a database and analyzing it.

[0970] "Means of collecting information from external sources" refers to the ability to obtain necessary news and weather information from external APIs and databases.

[0971] "Means for editing the generated script" refers to a function for manually or automatically correcting and adjusting the generated content as needed.

[0972] "Means for transmitting voice data to the user's terminal" refers to a function for delivering the generated voice data to the user's smartphone or other device.

[0973] "Means of using a generative AI model to provide voice information" refers to technology that uses generative AI to generate voice information appropriate for the user.

[0974] "Means for collecting and storing user feedback" refers to a function that obtains user ratings and opinions and stores them in a database.

[0975] "Means for analyzing feedback and improving the overall operation of the system" refers to a function for analyzing collected feedback to improve system performance and user satisfaction.

[0976] "Means for adjusting the output content of the generative AI model using the results of behavior analysis" refers to a function that optimizes the parameters and output of the generative AI based on the analysis results.

[0977] This invention relates to a voice information providing system that allows users to efficiently obtain necessary information and prevent "smartphone use while sleeping." This system is realized by combining the following main functions.

[0978] First, the server collects user interest and schedule information, stores it in a database, and analyzes it. Users launch the radio app on their smartphone and input their news categories of interest (e.g., sports, entertainment, business, etc.) and daily schedule information. This identifies the user's individual needs.

[0979] The server then sends requests to external news and weather APIs to gather the latest news articles and weather information, which is then filtered based on the user's interests.

[0980] Based on the collected information, the server uses a generative AI model to automatically generate a personalized radio show script suitable for the user. The script is created by inputting the generative AI model using prompt sentences such as the following:

[0981] "User is interested in sports and entertainment. Generate a personalized newscast script with the latest news and this morning's schedule information."

[0982] The generated script is converted into audio data using a server-based text-to-speech (TTS) engine. In this case, we use Google Cloud Text-to-Speech.

[0983] The generated audio data is then sent from the server to the user's device, where it is prepared for playback by the smartphone app, allowing the user to listen to personalized radio-style audio content through the app.

[0984] Furthermore, after listening to the audio content, users can enter feedback and ratings within the app. The device then sends this feedback to the server, which then stores the feedback information in a database for analysis. The results of this analysis are used to adjust the generative AI model and improve the overall system's operation.

[0985] For example, when a user wakes up in the morning and launches the radio app on their smartphone, an automatically generated radio program will play along with a friendly message like, "Good morning, user." The server generates the script for this radio program based on the latest news, weather information, and the user's schedule (e.g., work meetings), allowing the user to efficiently obtain the information they need without having to look at their smartphone screen.

[0986] This system prevents users from using their smartphones while sleeping and allows them to efficiently obtain the information they need.

[0987] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0988] Step 1:

[0989] Collecting user information

[0990] A user opens a radio app on their smartphone and enters the news categories they are interested in (sports, entertainment, business, etc.) and their daily schedule information. This information is input data and is important for identifying the user's individual needs. This information is sent to a server for subsequent information collection and analysis.

[0991] Step 2:

[0992] Saving and analyzing user information

[0993] The server stores the information entered by the user (such as name, interests, schedule, etc.) in a database. This information is then analyzed and output to identify user interests and behavioral patterns. The results of this analysis are used in the next news gathering process.

[0994] Step 3:

[0995] Gathering external information

[0996] The server sends requests to external news and weather APIs to retrieve the latest news articles and weather information. This is the input data. The collected information is filtered based on the user's interests and stored in a database as personalized information. This is the output data.

[0997] Step 4:

[0998] Automatic generation of radio program scripts

[0999] The server automatically generates a radio show script using a generative AI model based on the saved user information and collected external information. Specifically, it inputs the following prompt sentences into the generative AI model (e.g., GPT-3):

[1000] "User is interested in sports and entertainment. Generate a personalized newscast script with the latest news and this morning's schedule information."

[1001] The generated script becomes the output data.

[1002] Step 5:

[1003] Script audio conversion

[1004] The server converts the generated radio program script into audio data using a TTS (Text-To-Speech) engine (e.g., Google Cloud Text-to-Speech). The input data is the generated script, and the output data is audio data. The audio data is optimized for user listening.

[1005] Step 6:

[1006] Audio data distribution

[1007] The server sends the audio data to the user's device. The device receives the audio data and prepares it for playback. The user can listen to personalized radio programs through the radio app. The delivery of the audio data is the output data.

[1008] Step 7:

[1009] Gathering feedback

[1010] After listening to the audio content, users enter their feedback and ratings within the app. This is the input data. This feedback is sent from the device to the server and stored in the database. This is the output data.

[1011] Step 8:

[1012] Analyzing feedback and improving the system

[1013] The server analyzes the collected feedback and adjusts the output of the generative AI model based on the results. This improves the overall operation of the system and enables the provision of voice information that better meets the user's needs. The analyzed feedback data is the output data.

[1014] The above are the specific processing steps of the system, which is a mechanism for efficiently providing personalized voice information to users.

[1015] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1016] The present invention relates to a voice information provision system that allows users to efficiently obtain necessary information and prevents them from using their smartphones while sleeping. The system includes a generating means, a collecting means, an automatic generating means, a converting means to voice, a distributing means, a means for storing and analyzing user information, a means for collecting information from external sources, a means for editing the generated script, a means for transmitting voice data to the user's device, a means for collecting and storing user feedback, a means for analyzing the feedback and improving the overall operation of the system, and an emotion engine for recognizing user emotions.

[1017] 1. Entering and saving user information

[1018] User: Launches the radio app and accesses the account registration or login screen. Enters the news category of interest (sports, entertainment, business, etc.), daily schedule information, name, email address, and password.

[1019] Terminal: Sends the information entered by the user (name, email address, password, news category, schedule information) to the server.

[1020] Server: Stores and analyzes user information in a database. Updates user profiles based on interests and schedule information.

[1021] 2. Collection of information

[1022] Server: Sends requests to external news and weather APIs to collect the latest news articles and weather information.

[1023] 3. Automatic Generation of Radio Programs

[1024] Server: Using AI generated from saved user interest and schedule information and past viewing history, the server automatically generates radio program scripts suited to the user.

[1025] 4. Convert to audio data

[1026] Server: The generated radio program script is converted into voice data using a TTS (Text-To-Speech) engine.

[1027] 5. Audio data distribution

[1028] Server: Sends the generated voice data to the user's device.

[1029] Device: Prepares the received audio data for playback, allowing users to listen to radio-style audio content through the app.

[1030] 6. Emotion Recognition by Emotion Engine

[1031] User: By providing voice input through the microphone while using the Radio app at designated times and events.

[1032] Device: Sends the user's voice input to the server.

[1033] Server: Using the emotion engine, recognize emotions from the user's voice input. The recognized emotions are stored in a database and reflected in the user profile.

[1034] 7. Adjust your script based on emotion

[1035] Server: Based on the user's emotional information, the generative AI adjusts the content of the radio program script. For example, if the user is feeling stressed, it will adjust the script to include more relaxing topics and music.

[1036] 8. Feedback Collection and Analysis

[1037] Users: After listening to the audio content, they provide feedback and ratings within the app.

[1038] Terminal: Sends the entered feedback to the server.

[1039] Server: Feedback information is stored in a database and analyzed to improve the system's operation and the script generation process.

[1040] For example, when a user wakes up in the morning, they launch a radio app on their smartphone. The device starts playing an automatically generated radio program along with a friendly message like "Good morning, user." The server generates a script for this radio program based on the latest news, weather information, and the user's schedule (e.g., work meetings). Furthermore, the emotion engine recognizes the user's emotions through their voice input and adjusts the script content based on those emotions. By listening to this, users can efficiently obtain the information they need without having to look at their smartphone screen.

[1041] This system prevents users from using their smartphones while sleeping and allows them to efficiently obtain the information they need. It also provides a more personalized experience by providing content that matches the user's emotions with an emotion engine.

[1042] The processing flow will be explained below.

[1043] Step 1:

[1044] User: Launches the radio app and accesses the account registration or login screen. Enters the news category of interest (sports, entertainment, business, etc.), daily schedule information, name, email address, and password.

[1045] Step 2:

[1046] Terminal: Sends information entered by the user to the server, including name, email address, password, news category, and schedule information.

[1047] Step 3:

[1048] Server: Stores and analyzes user information in a database. Updates user profiles based on interests and schedule information.

[1049] Step 4:

[1050] Server: Sends requests to external news and weather APIs to collect the latest news articles and weather information.

[1051] Step 5:

[1052] Server: Using AI technology to automatically generate radio program scripts tailored to each user based on their saved interests, schedule, and past listening history. The scripts include greeting messages, the latest news, weather information, and schedule reminders.

[1053] Step 6:

[1054] Server: The generated radio program script is converted into voice data using a TTS (Text-To-Speech) engine.

[1055] Step 7:

[1056] Server: Sends the generated voice data to the user's device.

[1057] Step 8:

[1058] Device: Prepares the received audio data for playback, allowing users to listen to radio-style audio content through the app.

[1059] Step 9:

[1060] User: By providing voice input through the microphone while using the Radio app at designated times and events.

[1061] Step 10:

[1062] Device: Sends the user's voice input to the server.

[1063] Step 11:

[1064] Server: Using the emotion engine, recognize emotions from the user's voice input. The recognized emotions are stored in a database and reflected in the user profile.

[1065] Step 12:

[1066] Server: Based on the user's emotional information, the generative AI adjusts the content of the radio program script. For example, if the user is feeling stressed, it will adjust the script to include more relaxing topics and music.

[1067] Step 13:

[1068] Terminal: Receives the voice data generated based on the contents of the readjusted script.

[1069] Step 14:

[1070] Device: Prepares for playback and allows the user to listen to tailored radio-style audio content.

[1071] Step 15:

[1072] Users: After listening to the audio content, they provide feedback and ratings within the app.

[1073] Step 16:

[1074] Terminal: Sends the entered feedback to the server.

[1075] Step 17:

[1076] Server: Feedback information is stored in a database and analyzed to improve the system's operation and the script generation process.

[1077] Example 2

[1078] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1079] In today's information society, users need ways to efficiently obtain the information they need. However, many users have the habit of staring at their smartphone screens for long periods of time, which can lead to health problems such as decreased eyesight and poor posture. Furthermore, there is a lack of personalized information delivery systems that match the interests and emotions of individual users. Therefore, there is a need for a system that can provide information tailored to each user's needs, prevent smartphone use while sleeping, and reduce the impact on health.

[1080] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a generation means, an information collection means, an automatic generation means, a voice conversion means, and a distribution means. This allows the user to efficiently obtain the necessary information without using their eyes. In addition, since the server includes an emotion recognition means that recognizes the user's emotion and a script adjustment means that adjusts the script content based on the recognized emotion, it is possible to provide personalized information and increase user satisfaction.

[1081] A "generation means" is a device or process that has the function of creating data or content based on specified information.

[1082] An "information gathering tool" is a device or process that obtains the required data from an external source.

[1083] An "automatic generation means" is a device or process that has the ability to automatically generate content using artificial intelligence or algorithms based on collected data and user information.

[1084] "Speech conversion means" means a device or process that converts generated text data into speech data, such as a text-to-speech (TTS) engine.

[1085] A "delivery mechanism" is a device or process that transmits generated or converted audio data to a user's device.

[1086] "User information storage means" refers to a device or process that has the function of storing information provided by a user in a database or the like.

[1087] An "external information gathering means" is a device or process that obtains the latest news, weather information, etc. from external sources.

[1088] "Script editing means" refers to a device or process that has the function of editing and adjusting the generated script based on the user's needs and feelings.

[1089] "Audio data transmission means" is a device or process capable of transmitting generated audio data to a user's device.

[1090] A "user feedback collection means" is a device or process that has the function of collecting user ratings and opinions.

[1091] "Feedback analysis means" refers to a device or process that has the function of analyzing collected user feedback and using it to improve the system.

[1092] "Emotion recognition means" refers to a device or process that has the function of determining emotions from user voice input, etc.

[1093] A "script adjustment means" is a device or process that has the function of adjusting the script content of a radio program based on the recognized emotional information.

[1094] The present invention relates to a voice information provision system that allows users to efficiently obtain necessary information and prevents "smartphone use while sleeping." The system includes a generation unit, an information collection unit, an automatic generation unit, a voice conversion unit, and a distribution unit. It also includes a user information storage unit, an external information collection unit, a script editing unit, a voice data transmission unit, a user feedback collection unit, a feedback analysis unit, an emotion recognition unit, and a script adjustment unit.

[1095] First, the information provided by the user is sent from the device to a server. The server stores this information in a database and updates the user profile. For example, a user enters their name, email address, news categories of interest, and schedule information into a radio app. This information is sent from the device to the server, which stores it in a database such as MySQL and analyzes it.

[1096] The server then sends requests to external news or weather APIs to gather the latest news articles or weather information. For example, an HTTP GET request can be used to retrieve the latest articles from an external news API.

[1097] The server inputs prompts into the AI ​​model based on the saved user information, past viewing history, and external information, and automatically generates a radio program script. For example, the prompt could be: "Generate a radio program script that includes the latest news and weather forecast based on the user's interests."

[1098] The generated script is converted into voice data using a TTS (Text-To-Speech) engine in a voice conversion means on the server, for example, by using the Google Text-to-Speech API.

[1099] The server then delivers the audio data to the user's device. The audio data file is sent via an HTTP response, and the device receives the audio data, prepares it for playback, and starts playback using the media player API.

[1100] Furthermore, when a user uses the radio app at a specified time or event and inputs voice data through the microphone, the device sends this voice data to the server. The server uses emotion recognition to recognize emotions from the user's voice input, stores them in a database, and reflects them in the user profile. Based on the recognized emotion information, it inputs prompts to the generative AI model, such as "The user is feeling stressed, so please adjust the script to include relaxing topics and music." This allows the script content to be adjusted appropriately.

[1101] Finally, after listening to the audio content, the user can provide feedback and ratings, which are then sent to the server, which stores the feedback information in a database and analyzes it to improve the system's operation and script generation process.

[1102] For example, when a user wakes up in the morning and launches a radio app on their smartphone, an automatically generated radio program is played along with a friendly message such as "Good morning, user." The program includes information such as "Today's weather is sunny. The temperature is 20 degrees, with a maximum temperature of 25 degrees. Also, there is a meeting at 3 pm today, so don't forget to get ready." When the user asks, "What do you think about today's news?", the system recognizes the user's emotions and provides more relaxing topics based on the results.

[1103] Example prompt sentence:

[1104] "Generate radio show scripts with breaking news and weather forecasts based on user interests."

[1105] In this way, users can efficiently obtain the information they need without looking at their smartphone screen, and can receive information that is tailored to their emotions.

[1106] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1107] Step 1:

[1108] The user launches the radio app and accesses the account registration screen or login screen. The user enters their name, email address, password, and news categories of interest (daily schedule information). This is the input information. The device sends the information entered by the user to the server. Specifically, it uses the REST API to send an HTTP POST request. At this time, the input data is the name, email address, password, news categories, and schedule information, and the output is an HTTP request containing this information.

[1109] Step 2:

[1110] The server stores the received user information in a database. Specifically, it uses a database such as MySQL to store the data using an INSERT query. It then updates the user profile based on this information. In this process, the input data is the user information sent from the device, and the output is the stored data and the updated user profile.

[1111] Step 3:

[1112] The server sends HTTP GET requests to external news APIs and weather information APIs to collect the latest news articles and weather information. The input data is the API request, and the output is the retrieved news articles and weather forecast data. This data is then analyzed within the server to extract the necessary information.

[1113] Step 4:

[1114] The server creates and inputs a prompt to the generative AI model based on user information, past viewing history, external information, etc. For example, the prompt might be, "Generate a radio program script that includes the latest news and weather forecast based on the user's interests." The input data is the user information and the prompt, and the output is the generated radio program script.

[1115] Step 5:

[1116] The server inputs the generated radio program script into a TTS (Text-To-Speech) engine and converts it into voice data. As a concrete example, we will use the Google Text-to-Speech API. The input data is the generated script, and the output is voice data generated by the TTS engine.

[1117] Step 6:

[1118] The server sends the generated audio data to the user's device. For example, it sends an audio data file as an HTTP response, and the device receives the audio data and prepares for playback. Specifically, it starts playback using a media player API. The input data is the audio data, and the output is the audio that is received and played.

[1119] Step 7:

[1120] The user uses the radio app at a designated time or event and inputs voice through the microphone. The device sends this voice input data to the server. The input data is the user's voice, and the output is the voice input data sent to the server.

[1121] Step 8:

[1122] The server uses emotion recognition means to recognize emotions from the user's voice input. For example, using an emotion analysis API, it obtains the result "The user is relaxed." The input data is the voice input data, and the output is the analyzed emotion information. This is saved in the database and reflected in the user profile.

[1123] Step 9:

[1124] The server inputs prompts to the generative AI model based on the recognized emotional information. For example, it might say, "The user is feeling stressed, so please adjust the prompts to include relaxing topics and music." The input data are the recognized emotional information and prompts, and the output is an adjusted radio program script.

[1125] Step 10:

[1126] After listening to the audio content, the user inputs feedback and ratings within the app. The device sends this feedback to the server. The input data is the feedback, and the output is the feedback data sent to the server.

[1127] Step 11:

[1128] The server stores the feedback information in a database and analyzes it, which improves the system's behavior and the generation process. The input data is the feedback information, and the output is the analysis results and a list of improvements.

[1129] This is the specific processing flow of this system. This series of steps allows users to efficiently obtain the information they need without using their vision, and also provides them with personalized information that matches their emotions.

[1130] (Application example 2)

[1131] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1132] In modern society, many people operate smart devices while lying down, which often leads to poor sleep quality and health problems. Furthermore, it is difficult to efficiently obtain necessary information, which contributes to stress in daily life. The purpose of this invention is to solve these problems and support a healthy lifestyle while enabling users to efficiently obtain necessary information.

[1133] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting and saving user information, means for collecting information from external information sources, means for automatically generating a radio program script based on the user's interests and schedule information, means for converting the generated script into audio data, means for distributing the audio data, means for recognizing emotions from the user's voice input, means for adjusting the script content based on the recognized emotions, and means for collecting and analyzing user feedback. This allows users to efficiently obtain necessary information without looking at the screen of their smart device, preventing them from using their smartphone while sleeping. Furthermore, providing personalized content based on emotions is expected to reduce stress and improve quality of life.

[1134] "Means for inputting and storing user information" refers to the means by which a user inputs information about their interests and schedule and stores it in a database.

[1135] "Means of collecting information from external sources" refers to means of collecting the latest information using APIs, etc., to obtain external news and weather information.

[1136] "Means for automatically generating radio program scripts based on user interests and schedule information" means means for a generative AI model to use user profile data to create radio program scripts that are appropriate for the user.

[1137] The "means for converting the generated script into voice data" refers to a means for converting the generated script in text form into voice data using a TTS (Text-To-Speech) engine.

[1138] "Means for distributing audio data" refers to means for transmitting the generated audio data to a user's smartphone or other device and distributing audio content.

[1139] The "means for recognizing emotions from user voice input" refers to a means for analyzing emotions from the user's voice using an emotion engine and acquiring emotion data.

[1140] "Means for adjusting script content based on recognized emotions" refers to a means by which the generative AI model dynamically changes the script content of a radio program based on the acquired emotional data.

[1141] "Means for collecting and analyzing user feedback" refers to the means for storing the ratings and opinions provided by users in a database and analyzing them to help improve the system.

[1142] This invention provides a voice information provision system that allows users to efficiently obtain necessary information and prevents excessive use of smart devices. The system generates personalized voice content based on the user's interests and schedule information, and adjusts the content by recognizing the user's emotions.

[1143] Hardware and Software Used

[1144] The system of the present invention uses a server, user devices (smartphones, tablets, etc.), and various APIs (news API, weather information API, etc.). The server performs the main processing and performs various data processing and calculations using advanced software tools such as generative AI models, TTS (Text-To-Speech) engines, and emotion recognition engines.

[1145] Processing flow

[1146] 1. User information input and storage:

[1147] The server stores the name, email address, interest categories, schedule information, etc. that the user entered when registering an account in a database. This information is analyzed by the server and reflected in the user profile.

[1148] 2. Collection of Information:

[1149] The server sends requests to external news and weather APIs to collect the latest news articles and weather information in real time.

[1150] 3. Automatic generation of radio program scripts:

[1151] Based on the collected information and the user's profile, the server uses a generative AI model to automatically generate a radio program script suitable for the user, including news related to the user's interests and necessary schedule information.

[1152] 4. Conversion to audio data:

[1153] The server converts the generated script into audio data using a TTS engine, which can be heard by the user without any visual intervention.

[1154] 5. Audio data delivery:

[1155] The server transmits the generated voice data to the user's terminal, and the terminal plays back the received voice data.

[1156] 6. Emotion recognition:

[1157] When a user makes a voice input, the device sends the voice data to the server, which uses an emotion engine to recognize the user's emotion from the voice data and stores the information in a database.

[1158] 7. Content adjustment based on emotions:

[1159] The server uses the generative AI model to adjust the radio program script based on the recognized emotion data, for example, by including more relaxing topics and music if the user is feeling stressed.

[1160] 8. Feedback Collection and Analysis:

[1161] After listening to the audio content, users can input feedback, which is then sent to the server, which then stores the collected feedback in a database and analyzes it to improve the overall operation of the system.

[1162] Examples and prompts

[1163] As a concrete example, the following shows a specific case where a news API and sentiment model are utilized.

[1164] 1. News gathering examples:

[1165] Send a request to the URL https: / / newsapi.org / v2 / top-headlines?country=jp&category=technology&apiKey=your_news_api_key to get the latest technology news.

[1166] 2. Example prompt sentences for emotion recognition model:

[1167] In response to a user's voice input of "How's the weather today?", the emotion recognition engine generates a script to reply, "The weather is sunny today. It looks like you'll have a pleasant time."

[1168] Through these steps, the system of the present invention can efficiently provide necessary information to users while promoting healthy device use.

[1169] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1170] Step 1:

[1171] A user uses a smart device to provide input information (name, email address, password, interest categories, schedule information) on an account registration screen or login screen. The device sends this input information to a server. The server stores the received user information in a database and analyzes the information to build a user profile. The input is the user information, and the output is the user profile stored in the database.

[1172] Step 2:

[1173] The server periodically sends requests to external APIs (such as news APIs and weather APIs) to collect the latest information based on the user's interests. This collected data is used to generate personalized information based on the user profile. The input is news and weather data retrieved from the APIs, and the output is the latest information stored on the server.

[1174] Step 3:

[1175] The server automatically generates radio show scripts using a generative AI model based on user interests and schedule information, including incorporating collected news and weather information and processing the data to reflect user interests. The inputs are the user profile and collected external data, and the output is the generated radio show script.

[1176] Step 4:

[1177] The server converts the generated radio program script into voice data using a TTS (Text-To-Speech) engine, which generates natural-sounding voice from the text data. The input is the generated script text, and the output is the generated voice data.

[1178] Step 5:

[1179] The server sends the generated audio data to the user's device. The device prepares the received audio data for playback, allowing the user to listen to the audio content through the app. The input is the generated audio data, and the output is the audio data sent to the user's device.

[1180] Step 6:

[1181] While listening to audio content, a user provides emotional information through voice input. The device sends this voice data to a server, which then uses an emotion engine to recognize the user's emotion and stores the information in a database. The input is the user's voice input, and the output is the recognized emotional data.

[1182] Step 7:

[1183] The server uses the recognized emotion data to tailor the radio show script using a generative AI model. For example, if the user's stress level is high, the server might include more relaxing topics and music. The input is the recognized emotion data, and the output is the tailored radio show script.

[1184] Step 8:

[1185] After listening to the audio content, the user inputs feedback. The terminal sends this feedback information to the server, which then stores the collected feedback in a database and analyzes it to improve the system's operation and the script generation process. The input is the user's feedback, and the output is the feedback information stored in the database and its analysis results.

[1186] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1187] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1188] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1189] [Fourth embodiment]

[1190] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1191] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1192] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1193] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1194] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1195] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1196] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1197] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1198] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1199] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1200] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1201] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1202] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1203] The present invention relates to a voice information provision system that allows users to efficiently obtain necessary information and prevents them from using their smartphones while sleeping. The system includes a generating means, a collecting means, an automatic generating means, a converting means to voice, a distributing means, a means for storing and analyzing user information, a means for collecting information from external sources, a means for editing the generated script, a means for transmitting voice data to the user's device, a means for collecting and storing user feedback, and a means for analyzing the feedback and improving the operation of the entire system.

[1204] 1. Entering and saving user information

[1205] User: Launches the radio app and accesses the account registration or login screen. Enters the news categories of interest (sports, entertainment, business, etc.) and daily schedule information.

[1206] Device: Sends information entered by the user (such as name, email address, and password), as well as interests and schedule information, to the server.

[1207] Server: Stores user information in a database and analyzes it.

[1208] 2. Collection of information

[1209] Server: Sends requests to external news and weather APIs to collect the latest news articles and weather information.

[1210] 3. Automatic Generation of Radio Programs

[1211] Server: Based on the user's saved interest and schedule information and past viewing history, generative AI is used to automatically generate radio program scripts suitable for the user.

[1212] 4. Convert to audio data

[1213] Server: The generated radio program script is converted into voice data using a TTS (Text-To-Speech) engine.

[1214] 5. Audio data distribution

[1215] Server: Sends the generated voice data to the user's device.

[1216] Device: Prepares the received audio data for playback, allowing users to listen to radio-style audio content through the app.

[1217] 6. Feedback Collection and Analysis

[1218] Users: After listening to the audio content, they provide feedback and ratings within the app.

[1219] Terminal: Sends the entered feedback to the server.

[1220] Server: Feedback information is stored in a database and analyzed to improve the system's operation and the script generation process.

[1221] For example, when a user wakes up in the morning, they launch a radio app on their smartphone. The device starts playing an automatically generated radio program along with a friendly message like "Good morning, user." The server generates the script for this radio program based on the latest news, weather information, and the user's schedule (e.g., work meetings). By listening to this, the user can efficiently obtain the information they need without having to look at their smartphone screen.

[1222] This system prevents users from using their smartphones while sleeping and allows them to efficiently obtain the information they need.

[1223] The processing flow will be explained below.

[1224] Step 1:

[1225] User: Launches the radio app and accesses the account registration or login screen. Enters the news category of interest (sports, entertainment, business, etc.), daily schedule information, name, email address, and password.

[1226] Step 2:

[1227] Terminal: Sends information entered by the user to the server, including name, email address, password, news category, and schedule information.

[1228] Step 3:

[1229] Server: Stores and analyzes user information in a database. Updates user profiles based on interests and schedule information.

[1230] Step 4:

[1231] Server: Sends requests to external news and weather APIs to collect the latest news articles and weather information.

[1232] Step 5:

[1233] Server: Using AI technology, the server automatically generates radio program scripts tailored to each user based on their saved interests, schedule, and past listening history. The scripts include greeting messages, the latest news, weather information, and schedule reminders.

[1234] Step 6:

[1235] Server: The generated radio program script is converted into voice data using a TTS (Text-To-Speech) engine.

[1236] Step 7:

[1237] Server: Sends the generated voice data to the user's device.

[1238] Step 8:

[1239] Device: Prepares to play the received audio data, allowing users to listen to radio-style audio content through the app.

[1240] Step 9:

[1241] Users: After listening to the audio content, they provide feedback and ratings within the app.

[1242] Step 10:

[1243] Terminal: Sends the entered feedback to the server.

[1244] Step 11:

[1245] Server: Feedback information is stored in a database and analyzed to improve the system's operation and the script generation process.

[1246] Example 1

[1247] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1248] In modern society, many users use smartphones to gather information, but in certain situations (e.g., using a smartphone while lying down), it can be difficult to see the screen. This situation can have a negative impact on users' lifestyles and health. Furthermore, it can be difficult to select and efficiently gather information, making it difficult for users to quickly obtain the information they need.

[1249] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1250] In this invention, the server includes means for saving and analyzing information entered by the user, means for collecting data from external information sources, means for generating a script based on the collected data, means for converting the generated script into audio data, and means for delivering the audio data, thereby enabling the user to efficiently obtain necessary information by voice without looking at the screen.

[1251] "Means for storing and analyzing information entered by users" refers to a device or system that stores data entered by users, such as personal information, interests, and schedules, analyzes that data, and uses it to generate appropriate content.

[1252] A "means for collecting data from external sources" is a device or system that collects up-to-date information from external data sources such as news APIs or weather APIs.

[1253] "Means for generating scripts based on collected data" refers to a device or system that automatically creates appropriate radio program scripts for users using a generative AI model based on collected news, weather information, etc.

[1254] The "means for converting the generated script into voice data" refers to a device or system that converts the generated text-format script into voice data using a TTS (Text-to-Speech) engine.

[1255] "Means for distributing audio data" refers to a device or system that transmits the converted audio data to the user's terminal so that it can be played back.

[1256] "Means for editing a generated script" refers to a device or system that manually or automatically modifies and edits an automatically generated script.

[1257] "Feedback collection and storage means" means a device or system that collects and stores user ratings and opinions within the app.

[1258] A "means for analyzing feedback and improving overall system operation" is a device or system that analyzes collected feedback information and optimizes system operation or the content generation process based on that information.

[1259] "Server" refers to a central processing unit or the entire system for executing and managing all of the above means.

[1260] The present invention is a voice information provision system that allows users to efficiently obtain necessary information and prevents them from using their smartphones while sleeping. This system includes processes from user information input to voice data delivery and even feedback collection and analysis. Specific embodiments of the system are described below.

[1261] Feature Overview

[1262] 1. Entering and saving user information

[1263] User: Using a device such as a smartphone or tablet, the user launches a radio app and accesses the account registration or login screen, where they enter their name, email address, password, or the news category of their interest (e.g., sports, entertainment, business), as well as their daily schedule information.

[1264] Terminal: Validates the information entered by the user to ensure it is in the correct format, then sends this information to the server.

[1265] Server: Receives the transmitted information and stores it in a database. The stored information is used in the next process.

[1266] 2. Collection of information

[1267] Server: Sends requests to external news APIs (e.g., Google News API) or weather APIs (e.g., OpenWeatherMap API) and collects the necessary data.

[1268] 3. Automatic Generation of Radio Programs

[1269] Server: Based on the collected data, a generative AI model (e.g., OpenAI GPT-4) is used to automatically generate a radio program script. The following are examples of prompts for the AI ​​model:

[1270] User name: Yamada Taro

[1271] Interesting news categories: Business, Technology

[1272] Daily schedule: Meeting at 8am

[1273] Prompt statement:

[1274] "Generate a morning news radio show for user Taro Yamada. The categories are business and technology, and the schedule includes a meeting at 8am."

[1275] 4. Convert to audio data

[1276] Server: The generated radio program script is converted into audio data using a TTS (Text-To-Speech) engine (e.g., Google Text-to-Speech API).

[1277] 5. Audio data distribution

[1278] Server: Sends the generated voice data to the user's device.

[1279] Device: Receives audio data, prepares it for playback, and allows users to listen to radio-style audio content through the app.

[1280] 6. Feedback Collection and Analysis

[1281] Users: After listening to the audio content, they provide feedback and ratings within the app.

[1282] Terminal: Sends the entered feedback to the server.

[1283] Server: Stores the feedback information in a database and analyzes it. Based on the analysis results, the overall system behavior and content generation process are improved.

[1284] Specific examples

[1285] When a user wakes up in the morning, they launch the radio app on their smartphone. The device starts playing an automatically generated radio program along with a friendly message like "Good morning, user." The server generates the script for this radio program based on the latest news, weather information, and the user's schedule (e.g., work meetings). By listening to this, users can efficiently obtain the information they need without looking at their smartphone screen. This system prevents users from "using their smartphone while sleeping" and allows them to efficiently obtain the information they need.

[1286] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1287] System processing steps

[1288] Step 1: Enter and save user information

[1289] User: Launches a radio app using a smartphone or tablet device, accesses the account registration or login screen, and enters their name, email address, password, news categories of interest (e.g., sports, entertainment, business), and daily schedule information.

[1290] Input: Personal information, interests, and schedule information entered by the user.

[1291] Output: Information entered into the terminal is saved.

[1292] Terminal: Validates the information entered by the user to ensure it is in the correct format, and after successful validation, sends the information to the server.

[1293] Input: Information entered by the user.

[1294] Data processing: Input validation (e.g., checking email address format, password strength).

[1295] Output: Information ready to be sent to the server.

[1296] Server: Receives the information sent from the device and stores it in a database, which makes the data available for subsequent processing.

[1297] Input: User information sent from the device.

[1298] Data processing: Data storage.

[1299] Output: User information stored in the database.

[1300] Step 2: Gather information

[1301] Server: Sends requests to external news and weather APIs to collect the latest news articles and weather information.

[1302] Input: Information sent in the API request (user interest categories and region information).

[1303] Data processing: Generating and sending API requests.

[1304] Output: Collected news articles and weather information.

[1305] Server: Analyzes the collected information and stores it in a database in the form of news titles, summaries, weather forecasts, etc.

[1306] Input: Collected news articles and weather information.

[1307] Data processing: Analyzing data and organizing them into categories.

[1308] Output: Information stored in a database after analysis.

[1309] Step 3: Automatic generation of radio programs

[1310] Server: Automatically generates radio program scripts using a generative AI model based on user information in the database and collected news and weather information.

[1311] Input: User interests, news, and weather information stored in a database.

[1312] Data processing: Creating and sending prompts to generative AI models.

[1313] Output: A radio show script generated by the generative AI model.

[1314] For example, the prompt:

[1315] User name: Yamada Taro

[1316] Interesting news categories: Business, Technology

[1317] Daily schedule: Meeting at 8am

[1318] Prompt statement:

[1319] "Generate a morning news radio show for user Taro Yamada. The categories are business and technology, and the schedule includes a meeting at 8am."

[1320] Step 4: Convert to audio data

[1321] Server: The generated radio program script is converted into voice data using a TTS (Text-To-Speech) engine.

[1322] Input: A generated radio script.

[1323] Data processing: Voice data generation using a TTS engine.

[1324] Output: The generated audio data.

[1325] Step 5: Streaming audio data

[1326] Server: Sends the generated voice data to the user's device.

[1327] Input: The generated audio data.

[1328] Data processing: Preparing and sending audio data for distribution.

[1329] Output: The audio data sent to the device.

[1330] Device: Receives audio data and prepares it for playback, allowing users to listen to radio-style audio content through the app.

[1331] Input: Audio data received from the server.

[1332] Data processing: preparing for playback (e.g., caching, storing in memory).

[1333] Output: The audio content that is played to the user.

[1334] Step 6: Collect and analyze feedback

[1335] Users: After listening to the audio content, they provide feedback and ratings within the app.

[1336] Input: User input, such as ratings and feedback.

[1337] Output: Feedback typed into the terminal.

[1338] Terminal: Sends the entered feedback to the server.

[1339] Input: User feedback.

[1340] Data processing: packaging and sending feedback.

[1341] Output: Feedback sent to the server.

[1342] Server: Stores the feedback information in a database and analyzes it. Based on the analysis results, the system's behavior and content generation process are improved.

[1343] Input: Feedback sent from the device.

[1344] Data processing: Analysis of feedback and storage in a database.

[1345] Output: Improvements to system behavior and content generation processes.

[1346] (Application example 1)

[1347] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1348] Conventional voice information systems require users to manually search for information, which reduces the efficiency of information gathering and use. There are also concerns about the negative health effects of using a smartphone while sleeping. Furthermore, there is a lack of personalized information provision tailored to individual user needs, creating a need for improved user experience.

[1349] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1350] In this invention, the server includes a means for generating prompt sentences for generating and delivering voice information, a means for utilizing a generative AI model for providing the voice information, and a means for adjusting the output content of the generative AI model using the results of the behavior analysis, thereby enabling efficient and personalized voice information delivery according to the user's needs.

[1351] "Generative means" is the ability to create new information or content for a specific purpose.

[1352] "Means of collecting information" refers to the function of obtaining necessary data and news from external sources.

[1353] "Means for automatic generation" refers to the ability of the system to autonomously create content without the need for human intervention.

[1354] "Means for converting into voice" refers to technology for converting text data into voice data.

[1355] "Means of distribution" refers to the function of delivering the generated voice data and information to the user's device.

[1356] "Means for generating prompt sentences for generating and delivering voice information" refers to a function that automatically generates initial input (prompts) for the generative AI model to create personalized voice information.

[1357] A "server" is a computer system that processes requested information and manages data.

[1358] "Means for saving and analyzing user information" refers to the function of saving user interests and schedule information in a database and analyzing it.

[1359] "Means of collecting information from external sources" refers to the ability to obtain necessary news and weather information from external APIs and databases.

[1360] "Means for editing the generated script" refers to a function for manually or automatically correcting and adjusting the generated content as needed.

[1361] "Means for transmitting voice data to the user's terminal" refers to a function for delivering the generated voice data to the user's smartphone or other device.

[1362] "Means of using a generative AI model to provide voice information" refers to technology that uses generative AI to generate voice information appropriate for the user.

[1363] "Means for collecting and storing user feedback" refers to a function that obtains user ratings and opinions and stores them in a database.

[1364] "Means for analyzing feedback and improving the overall operation of the system" refers to a function for analyzing collected feedback to improve system performance and user satisfaction.

[1365] "Means for adjusting the output content of the generative AI model using the results of behavior analysis" refers to a function that optimizes the parameters and output of the generative AI based on the analysis results.

[1366] This invention relates to a voice information providing system that allows users to efficiently obtain necessary information and prevent "smartphone use while sleeping." This system is realized by combining the following main functions.

[1367] First, the server collects user interest and schedule information, stores it in a database, and analyzes it. Users launch the radio app on their smartphone and input their news categories of interest (e.g., sports, entertainment, business, etc.) and daily schedule information. This identifies the user's individual needs.

[1368] The server then sends requests to external news and weather APIs to gather the latest news articles and weather information, which is then filtered based on the user's interests.

[1369] Based on the collected information, the server uses a generative AI model to automatically generate a personalized radio show script suitable for the user. The script is created by inputting the generative AI model using prompt sentences such as the following:

[1370] "User is interested in sports and entertainment. Generate a personalized newscast script with the latest news and this morning's schedule information."

[1371] The generated script is converted into audio data using a server-based text-to-speech (TTS) engine. In this case, we use Google Cloud Text-to-Speech.

[1372] The generated audio data is then sent from the server to the user's device, where it is prepared for playback by the smartphone app, allowing the user to listen to personalized radio-style audio content through the app.

[1373] Furthermore, after listening to the audio content, users can enter feedback and ratings within the app. The device then sends this feedback to the server, which then stores the feedback information in a database for analysis. The results of this analysis are used to adjust the generative AI model and improve the overall system's operation.

[1374] For example, when a user wakes up in the morning and launches the radio app on their smartphone, an automatically generated radio program will play along with a friendly message like, "Good morning, user." The server generates the script for this radio program based on the latest news, weather information, and the user's schedule (e.g., work meetings), allowing the user to efficiently obtain the information they need without having to look at their smartphone screen.

[1375] This system prevents users from using their smartphones while sleeping and allows them to efficiently obtain the information they need.

[1376] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1377] Step 1:

[1378] Collecting user information

[1379] A user opens a radio app on their smartphone and enters the news categories they are interested in (sports, entertainment, business, etc.) and their daily schedule information. This information is input data and is important for identifying the user's individual needs. This information is sent to a server for subsequent information collection and analysis.

[1380] Step 2:

[1381] Saving and analyzing user information

[1382] The server stores the information entered by the user (such as name, interests, schedule, etc.) in a database. This information is then analyzed and output to identify user interests and behavioral patterns. The results of this analysis are used in the next news gathering process.

[1383] Step 3:

[1384] Gathering external information

[1385] The server sends requests to external news and weather APIs to retrieve the latest news articles and weather information. This is the input data. The collected information is filtered based on the user's interests and stored in a database as personalized information. This is the output data.

[1386] Step 4:

[1387] Automatic generation of radio program scripts

[1388] The server automatically generates a radio show script using a generative AI model based on the saved user information and collected external information. Specifically, it inputs the following prompt sentences into the generative AI model (e.g., GPT-3):

[1389] "User is interested in sports and entertainment. Generate a personalized newscast script with the latest news and this morning's schedule information."

[1390] The generated script becomes the output data.

[1391] Step 5:

[1392] Script audio conversion

[1393] The server converts the generated radio program script into audio data using a TTS (Text-To-Speech) engine (e.g., Google Cloud Text-to-Speech). The input data is the generated script, and the output data is audio data. The audio data is optimized for user listening.

[1394] Step 6:

[1395] Audio data distribution

[1396] The server sends the audio data to the user's device. The device receives the audio data and prepares it for playback. The user can listen to personalized radio programs through the radio app. The delivery of the audio data is the output data.

[1397] Step 7:

[1398] Gathering feedback

[1399] After listening to the audio content, users enter their feedback and ratings within the app. This is the input data. This feedback is sent from the device to the server and stored in the database. This is the output data.

[1400] Step 8:

[1401] Analyzing feedback and improving the system

[1402] The server analyzes the collected feedback and adjusts the output of the generative AI model based on the results. This improves the overall operation of the system and enables the provision of voice information that better meets the user's needs. The analyzed feedback data is the output data.

[1403] The above are the specific processing steps of the system, which is a mechanism for efficiently providing personalized voice information to users.

[1404] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1405] The present invention relates to a voice information provision system that allows users to efficiently obtain necessary information and prevents them from using their smartphones while sleeping. The system includes a generating means, a collecting means, an automatic generating means, a converting means to voice, a distributing means, a means for storing and analyzing user information, a means for collecting information from external sources, a means for editing the generated script, a means for transmitting voice data to the user's device, a means for collecting and storing user feedback, a means for analyzing the feedback and improving the overall operation of the system, and an emotion engine for recognizing user emotions.

[1406] 1. Entering and saving user information

[1407] User: Launches the radio app and accesses the account registration or login screen. Enters the news category of interest (sports, entertainment, business, etc.), daily schedule information, name, email address, and password.

[1408] Terminal: Sends the information entered by the user (name, email address, password, news category, schedule information) to the server.

[1409] Server: Stores and analyzes user information in a database. Updates user profiles based on interests and schedule information.

[1410] 2. Collection of information

[1411] Server: Sends requests to external news and weather APIs to collect the latest news articles and weather information.

[1412] 3. Automatic Generation of Radio Programs

[1413] Server: Using AI generated from saved user interest and schedule information and past viewing history, the server automatically generates radio program scripts suited to the user.

[1414] 4. Convert to audio data

[1415] Server: The generated radio program script is converted into voice data using a TTS (Text-To-Speech) engine.

[1416] 5. Audio data distribution

[1417] Server: Sends the generated voice data to the user's device.

[1418] Device: Prepares the received audio data for playback, allowing users to listen to radio-style audio content through the app.

[1419] 6. Emotion Recognition by Emotion Engine

[1420] User: By providing voice input through the microphone while using the Radio app at designated times and events.

[1421] Device: Sends the user's voice input to the server.

[1422] Server: Using the emotion engine, recognize emotions from the user's voice input. The recognized emotions are stored in a database and reflected in the user profile.

[1423] 7. Adjust your script based on emotion

[1424] Server: Based on the user's emotional information, the generative AI adjusts the content of the radio program script. For example, if the user is feeling stressed, it will adjust the script to include more relaxing topics and music.

[1425] 8. Feedback Collection and Analysis

[1426] Users: After listening to the audio content, they provide feedback and ratings within the app.

[1427] Terminal: Sends the entered feedback to the server.

[1428] Server: Feedback information is stored in a database and analyzed to improve the system's operation and the script generation process.

[1429] For example, when a user wakes up in the morning, they launch a radio app on their smartphone. The device starts playing an automatically generated radio program along with a friendly message like "Good morning, user." The server generates a script for this radio program based on the latest news, weather information, and the user's schedule (e.g., work meetings). Furthermore, the emotion engine recognizes the user's emotions through their voice input and adjusts the script content based on those emotions. By listening to this, users can efficiently obtain the information they need without having to look at their smartphone screen.

[1430] This system prevents users from using their smartphones while sleeping and allows them to efficiently obtain the information they need. It also provides a more personalized experience by providing content that matches the user's emotions with an emotion engine.

[1431] The processing flow will be explained below.

[1432] Step 1:

[1433] User: Launches the radio app and accesses the account registration or login screen. Enters the news category of interest (sports, entertainment, business, etc.), daily schedule information, name, email address, and password.

[1434] Step 2:

[1435] Terminal: Sends information entered by the user to the server, including name, email address, password, news category, and schedule information.

[1436] Step 3:

[1437] Server: Stores and analyzes user information in a database. Updates user profiles based on interests and schedule information.

[1438] Step 4:

[1439] Server: Sends requests to external news and weather APIs to collect the latest news articles and weather information.

[1440] Step 5:

[1441] Server: Using AI technology to automatically generate radio program scripts tailored to each user based on their saved interests, schedule, and past listening history. The scripts include greeting messages, the latest news, weather information, and schedule reminders.

[1442] Step 6:

[1443] Server: The generated radio program script is converted into voice data using a TTS (Text-To-Speech) engine.

[1444] Step 7:

[1445] Server: Sends the generated voice data to the user's device.

[1446] Step 8:

[1447] Device: Prepares the received audio data for playback, allowing users to listen to radio-style audio content through the app.

[1448] Step 9:

[1449] User: By providing voice input through the microphone while using the Radio app at designated times and events.

[1450] Step 10:

[1451] Device: Sends the user's voice input to the server.

[1452] Step 11:

[1453] Server: Using the emotion engine, recognize emotions from the user's voice input. The recognized emotions are stored in a database and reflected in the user profile.

[1454] Step 12:

[1455] Server: Based on the user's emotional information, the generative AI adjusts the content of the radio program script. For example, if the user is feeling stressed, it will adjust the script to include more relaxing topics and music.

[1456] Step 13:

[1457] Terminal: Receives the voice data generated based on the contents of the readjusted script.

[1458] Step 14:

[1459] Device: Prepares for playback and allows the user to listen to tailored radio-style audio content.

[1460] Step 15:

[1461] Users: After listening to the audio content, they provide feedback and ratings within the app.

[1462] Step 16:

[1463] Terminal: Sends the entered feedback to the server.

[1464] Step 17:

[1465] Server: Feedback information is stored in a database and analyzed to improve the system's operation and the script generation process.

[1466] Example 2

[1467] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1468] In today's information society, users need ways to efficiently obtain the information they need. However, many users have the habit of staring at their smartphone screens for long periods of time, which can lead to health problems such as decreased eyesight and poor posture. Furthermore, there is a lack of personalized information delivery systems that match the interests and emotions of individual users. Therefore, there is a need for a system that can provide information tailored to each user's needs, prevent smartphone use while sleeping, and reduce the impact on health.

[1469] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a generation means, an information collection means, an automatic generation means, a voice conversion means, and a distribution means. This allows the user to efficiently obtain the necessary information without using their eyes. In addition, since the server includes an emotion recognition means that recognizes the user's emotion and a script adjustment means that adjusts the script content based on the recognized emotion, it is possible to provide personalized information and increase user satisfaction.

[1470] A "generation means" is a device or process that has the function of creating data or content based on specified information.

[1471] An "information gathering tool" is a device or process that obtains the required data from an external source.

[1472] An "automatic generation means" is a device or process that has the ability to automatically generate content using artificial intelligence or algorithms based on collected data and user information.

[1473] "Speech conversion means" means a device or process that converts generated text data into speech data, such as a text-to-speech (TTS) engine.

[1474] A "delivery mechanism" is a device or process that transmits generated or converted audio data to a user's device.

[1475] "User information storage means" refers to a device or process that has the function of storing information provided by a user in a database or the like.

[1476] An "external information gathering means" is a device or process that obtains the latest news, weather information, etc. from external sources.

[1477] "Script editing means" refers to a device or process that has the function of editing and adjusting the generated script based on the user's needs and feelings.

[1478] "Audio data transmission means" is a device or process capable of transmitting generated audio data to a user's device.

[1479] A "user feedback collection means" is a device or process that has the function of collecting user ratings and opinions.

[1480] "Feedback analysis means" refers to a device or process that has the function of analyzing collected user feedback and using it to improve the system.

[1481] "Emotion recognition means" refers to a device or process that has the function of determining emotions from user voice input, etc.

[1482] A "script adjustment means" is a device or process that has the function of adjusting the script content of a radio program based on the recognized emotional information.

[1483] The present invention relates to a voice information provision system that allows users to efficiently obtain necessary information and prevents "smartphone use while sleeping." The system includes a generation unit, an information collection unit, an automatic generation unit, a voice conversion unit, and a distribution unit. It also includes a user information storage unit, an external information collection unit, a script editing unit, a voice data transmission unit, a user feedback collection unit, a feedback analysis unit, an emotion recognition unit, and a script adjustment unit.

[1484] First, the information provided by the user is sent from the device to a server. The server stores this information in a database and updates the user profile. For example, a user enters their name, email address, news categories of interest, and schedule information into a radio app. This information is sent from the device to the server, which stores it in a database such as MySQL and analyzes it.

[1485] The server then sends requests to external news or weather APIs to gather the latest news articles or weather information. For example, an HTTP GET request can be used to retrieve the latest articles from an external news API.

[1486] The server inputs prompts into the AI ​​model based on the saved user information, past viewing history, and external information, and automatically generates a radio program script. For example, the prompt could be: "Generate a radio program script that includes the latest news and weather forecast based on the user's interests."

[1487] The generated script is converted into voice data using a TTS (Text-To-Speech) engine in a voice conversion means on the server, for example, by using the Google Text-to-Speech API.

[1488] The server then delivers the audio data to the user's device. The audio data file is sent via an HTTP response, and the device receives the audio data, prepares it for playback, and starts playback using the media player API.

[1489] Furthermore, when a user uses the radio app at a specified time or event and inputs voice data through the microphone, the device sends this voice data to the server. The server uses emotion recognition to recognize emotions from the user's voice input, stores them in a database, and reflects them in the user profile. Based on the recognized emotion information, it inputs prompts to the generative AI model, such as "The user is feeling stressed, so please adjust the script to include relaxing topics and music." This allows the script content to be adjusted appropriately.

[1490] Finally, after listening to the audio content, the user can provide feedback and ratings, which are then sent to the server, which stores the feedback information in a database and analyzes it to improve the system's operation and script generation process.

[1491] For example, when a user wakes up in the morning and launches a radio app on their smartphone, an automatically generated radio program is played along with a friendly message such as "Good morning, user." The program includes information such as "Today's weather is sunny. The temperature is 20 degrees, with a maximum temperature of 25 degrees. Also, there is a meeting at 3 pm today, so don't forget to get ready." When the user asks, "What do you think about today's news?", the system recognizes the user's emotions and provides more relaxing topics based on the results.

[1492] Example prompt sentence:

[1493] "Generate radio show scripts with breaking news and weather forecasts based on user interests."

[1494] In this way, users can efficiently obtain the information they need without looking at their smartphone screen, and can receive information that is tailored to their emotions.

[1495] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1496] Step 1:

[1497] The user launches the radio app and accesses the account registration screen or login screen. The user enters their name, email address, password, and news categories of interest (daily schedule information). This is the input information. The device sends the information entered by the user to the server. Specifically, it uses the REST API to send an HTTP POST request. At this time, the input data is the name, email address, password, news categories, and schedule information, and the output is an HTTP request containing this information.

[1498] Step 2:

[1499] The server stores the received user information in a database. Specifically, it uses a database such as MySQL to store the data using an INSERT query. It then updates the user profile based on this information. In this process, the input data is the user information sent from the device, and the output is the stored data and the updated user profile.

[1500] Step 3:

[1501] The server sends HTTP GET requests to external news APIs and weather information APIs to collect the latest news articles and weather information. The input data is the API request, and the output is the retrieved news articles and weather forecast data. This data is then analyzed within the server to extract the necessary information.

[1502] Step 4:

[1503] The server creates and inputs a prompt to the generative AI model based on user information, past viewing history, external information, etc. For example, the prompt might be, "Generate a radio program script that includes the latest news and weather forecast based on the user's interests." The input data is the user information and the prompt, and the output is the generated radio program script.

[1504] Step 5:

[1505] The server inputs the generated radio program script into a TTS (Text-To-Speech) engine and converts it into voice data. As a concrete example, we will use the Google Text-to-Speech API. The input data is the generated script, and the output is voice data generated by the TTS engine.

[1506] Step 6:

[1507] The server sends the generated audio data to the user's device. For example, it sends an audio data file as an HTTP response, and the device receives the audio data and prepares for playback. Specifically, it starts playback using a media player API. The input data is the audio data, and the output is the audio that is received and played.

[1508] Step 7:

[1509] The user uses the radio app at a designated time or event and inputs voice through the microphone. The device sends this voice input data to the server. The input data is the user's voice, and the output is the voice input data sent to the server.

[1510] Step 8:

[1511] The server uses emotion recognition means to recognize emotions from the user's voice input. For example, using an emotion analysis API, it obtains the result "The user is relaxed." The input data is the voice input data, and the output is the analyzed emotion information. This is saved in the database and reflected in the user profile.

[1512] Step 9:

[1513] The server inputs prompts to the generative AI model based on the recognized emotional information. For example, it might say, "The user is feeling stressed, so please adjust the prompts to include relaxing topics and music." The input data are the recognized emotional information and prompts, and the output is an adjusted radio program script.

[1514] Step 10:

[1515] After listening to the audio content, the user inputs feedback and ratings within the app. The device sends this feedback to the server. The input data is the feedback, and the output is the feedback data sent to the server.

[1516] Step 11:

[1517] The server stores the feedback information in a database and analyzes it, which improves the system's behavior and the generation process. The input data is the feedback information, and the output is the analysis results and a list of improvements.

[1518] This is the specific processing flow of this system. This series of steps allows users to efficiently obtain the information they need without using their vision, and also provides them with personalized information that matches their emotions.

[1519] (Application example 2)

[1520] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1521] In modern society, many people operate smart devices while lying down, which often leads to poor sleep quality and health problems. Furthermore, it is difficult to efficiently obtain necessary information, which contributes to stress in daily life. The purpose of this invention is to solve these problems and support a healthy lifestyle while enabling users to efficiently obtain necessary information.

[1522] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting and saving user information, means for collecting information from external information sources, means for automatically generating a radio program script based on the user's interests and schedule information, means for converting the generated script into audio data, means for distributing the audio data, means for recognizing emotions from the user's voice input, means for adjusting the script content based on the recognized emotions, and means for collecting and analyzing user feedback. This allows users to efficiently obtain necessary information without looking at the screen of their smart device, preventing them from using their smartphone while sleeping. Furthermore, providing personalized content based on emotions is expected to reduce stress and improve quality of life.

[1523] "Means for inputting and storing user information" refers to the means by which a user inputs information about their interests and schedule and stores it in a database.

[1524] "Means of collecting information from external sources" refers to means of collecting the latest information using APIs, etc., to obtain external news and weather information.

[1525] "Means for automatically generating radio program scripts based on user interests and schedule information" means means for a generative AI model to use user profile data to create radio program scripts that are appropriate for the user.

[1526] The "means for converting the generated script into voice data" refers to a means for converting the generated script in text form into voice data using a TTS (Text-To-Speech) engine.

[1527] "Means for distributing audio data" refers to means for transmitting the generated audio data to a user's smartphone or other device and distributing audio content.

[1528] The "means for recognizing emotions from user voice input" refers to a means for analyzing emotions from the user's voice using an emotion engine and acquiring emotion data.

[1529] "Means for adjusting script content based on recognized emotions" refers to a means by which the generative AI model dynamically changes the script content of a radio program based on the acquired emotional data.

[1530] "Means for collecting and analyzing user feedback" refers to the means for storing the ratings and opinions provided by users in a database and analyzing them to help improve the system.

[1531] This invention provides a voice information provision system that allows users to efficiently obtain necessary information and prevents excessive use of smart devices. The system generates personalized voice content based on the user's interests and schedule information, and adjusts the content by recognizing the user's emotions.

[1532] Hardware and Software Used

[1533] The system of the present invention uses a server, user devices (smartphones, tablets, etc.), and various APIs (news API, weather information API, etc.). The server performs the main processing and performs various data processing and calculations using advanced software tools such as generative AI models, TTS (Text-To-Speech) engines, and emotion recognition engines.

[1534] Processing flow

[1535] 1. User information input and storage:

[1536] The server stores the name, email address, interest categories, schedule information, etc. that the user entered when registering an account in a database. This information is analyzed by the server and reflected in the user profile.

[1537] 2. Collection of Information:

[1538] The server sends requests to external news and weather APIs to collect the latest news articles and weather information in real time.

[1539] 3. Automatic generation of radio program scripts:

[1540] Based on the collected information and the user's profile, the server uses a generative AI model to automatically generate a radio program script suitable for the user, including news related to the user's interests and necessary schedule information.

[1541] 4. Conversion to audio data:

[1542] The server converts the generated script into audio data using a TTS engine, which can be heard by the user without any visual intervention.

[1543] 5. Audio data delivery:

[1544] The server transmits the generated voice data to the user's terminal, and the terminal plays back the received voice data.

[1545] 6. Emotion recognition:

[1546] When a user makes a voice input, the device sends the voice data to the server, which uses an emotion engine to recognize the user's emotion from the voice data and stores the information in a database.

[1547] 7. Content adjustment based on emotions:

[1548] The server uses the generative AI model to adjust the radio program script based on the recognized emotion data, for example, by including more relaxing topics and music if the user is feeling stressed.

[1549] 8. Feedback Collection and Analysis:

[1550] After listening to the audio content, users can input feedback, which is then sent to the server, which then stores the collected feedback in a database and analyzes it to improve the overall operation of the system.

[1551] Examples and prompts

[1552] As a concrete example, the following shows a specific case where a news API and sentiment model are utilized.

[1553] 1. News gathering examples:

[1554] Send a request to the URL https: / / newsapi.org / v2 / top-headlines?country=jp&category=technology&apiKey=your_news_api_key to get the latest technology news.

[1555] 2. Example prompt sentences for emotion recognition model:

[1556] In response to a user's voice input of "How's the weather today?", the emotion recognition engine generates a script to reply, "The weather is sunny today. It looks like you'll have a pleasant time."

[1557] Through these steps, the system of the present invention can efficiently provide necessary information to users while promoting healthy device use.

[1558] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1559] Step 1:

[1560] A user uses a smart device to provide input information (name, email address, password, interest categories, schedule information) on an account registration screen or login screen. The device sends this input information to a server. The server stores the received user information in a database and analyzes the information to build a user profile. The input is the user information, and the output is the user profile stored in the database.

[1561] Step 2:

[1562] The server periodically sends requests to external APIs (such as news APIs and weather APIs) to collect the latest information based on the user's interests. This collected data is used to generate personalized information based on the user profile. The input is news and weather data retrieved from the APIs, and the output is the latest information stored on the server.

[1563] Step 3:

[1564] The server automatically generates radio show scripts using a generative AI model based on user interests and schedule information, including incorporating collected news and weather information and processing the data to reflect user interests. The inputs are the user profile and collected external data, and the output is the generated radio show script.

[1565] Step 4:

[1566] The server converts the generated radio program script into voice data using a TTS (Text-To-Speech) engine, which generates natural-sounding voice from the text data. The input is the generated script text, and the output is the generated voice data.

[1567] Step 5:

[1568] The server sends the generated audio data to the user's device. The device prepares the received audio data for playback, allowing the user to listen to the audio content through the app. The input is the generated audio data, and the output is the audio data sent to the user's device.

[1569] Step 6:

[1570] While listening to audio content, a user provides emotional information through voice input. The device sends this voice data to a server, which then uses an emotion engine to recognize the user's emotion and stores the information in a database. The input is the user's voice input, and the output is the recognized emotional data.

[1571] Step 7:

[1572] The server uses the recognized emotion data to tailor the radio show script using a generative AI model. For example, if the user's stress level is high, the server might include more relaxing topics and music. The input is the recognized emotion data, and the output is the tailored radio show script.

[1573] Step 8:

[1574] After listening to the audio content, the user inputs feedback. The terminal sends this feedback information to the server, which then stores the collected feedback in a database and analyzes it to improve the system's operation and the script generation process. The input is the user's feedback, and the output is the feedback information stored in the database and its analysis results.

[1575] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1576] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1577] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1578] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1579] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1580] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1581] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1582] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1583] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1584] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1585] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1586] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1587] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1588] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1589] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1590] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1591] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1592] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1593] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1594] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1595] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1596] The following is further disclosed regarding the above embodiment.

[1597] (Claim 1)

[1598] a generating means;

[1599] means of collection, and

[1600] a means for automatically generating

[1601] means for converting the signal into audio;

[1602] A means of delivery; and

[1603] A system including:

[1604] (Claim 2)

[1605] The means by which we store and analyze your information;

[1606] means of collecting information from external sources;

[1607] means for editing the generated script;

[1608] a means for transmitting the audio data to a user's device;

[1609] 10. The system of claim 1, further comprising:

[1610] (Claim 3)

[1611] A means of collecting and storing user feedback;

[1612] a means of analyzing the feedback and improving the overall system behavior;

[1613] 10. The system of claim 1, further comprising:

[1614] "Example 1"

[1615] (Claim 1)

[1616] A means for storing and analyzing information entered by users;

[1617] means of collecting data from external sources;

[1618] a means for generating a script based on the collected data;

[1619] means for converting the generated script into audio data;

[1620] means for delivering audio data;

[1621] A system including:

[1622] (Claim 2)

[1623] The means by which we store and analyze your information;

[1624] a means for obtaining data from external sources;

[1625] means for editing the generated script;

[1626] means for transmitting the audio data to a user's device;

[1627] 10. The system of claim 1, further comprising:

[1628] (Claim 3)

[1629] A means of collecting and storing user feedback;

[1630] a means of analyzing the feedback and improving the overall system behavior;

[1631] 10. The system of claim 1, further comprising:

[1632] "Application Example 1"

[1633] (Claim 1)

[1634] a generating means;

[1635] means of collecting information;

[1636] a means for automatically generating

[1637] means for converting the signal into audio;

[1638] A means of delivery; and

[1639] means for generating prompt sentences for generating and delivering audio information;

[1640] A system including:

[1641] (Claim 2)

[1642] The means by which we store and analyze your information;

[1643] means of collecting information from external sources;

[1644] means for editing the generated script;

[1645] means for transmitting the audio data to a user's device;

[1646] A means for utilizing a generative AI model to provide audio information; and

[1647] 10. The system of claim 1.

[1648] (Claim 3)

[1649] A means of collecting and storing user feedback;

[1650] a means of analyzing the feedback and improving the overall system behavior;

[1651] A means for adjusting the output content of the generative AI model using the results of the behavior analysis;

[1652] 10. The system of claim 1.

[1653] "Example 2: Combining Emotion Engines"

[1654] (Claim 1)

[1655] generating means;

[1656] Information gathering means;

[1657] an automatic generation means;

[1658] A voice conversion means;

[1659] A means of delivery;

[1660] A system including:

[1661] (Claim 2)

[1662] A user information storage means;

[1663] External information gathering means;

[1664] Script editing means;

[1665] audio data transmitting means;

[1666] 10. The system of claim 1, further comprising:

[1667] (Claim 3)

[1668] a means of collecting user feedback;

[1669] feedback analysis means;

[1670] 10. The system of claim 1, further comprising:

[1671] (Claim 4)

[1672] emotion recognition means for recognizing an emotion of a user;

[1673] a script adjusting means for adjusting the script content based on the recognized emotion;

[1674] 10. The system of claim 1, further comprising:

[1675] "Application example 2 when combining emotion engines"

[1676] (Claim 1)

[1677] A means of entering and storing user information;

[1678] means of collecting information from external sources;

[1679] means for automatically generating radio program scripts based on user interests and schedule information;

[1680] means for converting the generated script into audio data;

[1681] means for delivering audio data;

[1682] a means for recognizing emotions from a user's voice input;

[1683] a means for adjusting script content based on the recognized emotions;

[1684] means of collecting and analyzing user feedback;

[1685] A system including:

[1686] (Claim 2)

[1687] a means for transmitting the audio data to a user's device;

[1688] A means of automatically generating radio program scripts using generative AI,

[1689] using an emotion engine to recognize the emotion of a user;

[1690] 10. The system of claim 1, further comprising:

[1691] (Claim 3)

[1692] A means for converting the generated script content into voice data using a TTS (Text-To-Speech) engine;

[1693] A means of storing and analyzing feedback information in a database to improve the system's operation and the script generation process;

[1694] 10. The system of claim 1, further comprising: [Explanation of symbols]

[1695] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a generating means; means of collection, and a means for automatically generating means for converting the signal into audio; A means of delivery; and A system including:

2. The means by which we store and analyze your information; means of collecting information from external sources; means for editing the generated script; a means for transmitting the audio data to a user's device; The system of claim 1 further comprising:

3. A means of collecting and storing user feedback; a means of analyzing the feedback and improving the overall system behavior; The system of claim 1 further comprising:

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